Graph Learning Reading List
I scanned over the accepted paper lists of top machine learning and data mining conferences for interests in graph learning. If you are interested in dynamic (temporal) graph learning, please refer to Dynamic (Temporal) Graph Learning Reading List. We also add a snippset tutorial Parse Website to teach you how to obtain the titles and authors from the official conference website.
Contents
- IJCAI-2023 ICML-2023 KDD-2023 SIGIR-2023 AAAI-2023 ICLR-2023 WSDM-2023 WWW-2023 ICDE-2023 SIGMOD-2023
- IJCAI-2022 ICML-2022 KDD-2022 SIGIR-2022 NeurIPS-2022 AAAI-2022 ICLR-2022 WSDM-2022 WWW-2022 ICDE-2022 SIGMOD-2022
IJCAI-2023
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Self-supervised Graph Disentangled Networks for Review-based Recommendation
Yuyang Ren, Haonan Zhang, Qi Li, Luoyi Fu, Xinbing Wang, Chenghu Zhou
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A Canonicalization-Enhanced Known Fact-Aware Framework For Open Knowledge Graph Link Prediction
Yilin Wang, Minghao Hu, Zhen Huang, Dongsheng Li, Wei Luo, Dong Yang, Xicheng Lu
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KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach
Yi Wu, Yanyang Xu, Wenhao Zhu, Guojie Song, Zhouchen Lin, Liang Wang, Shaoguo Liu
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Multi-level Graph Contrastive Prototypical Clustering
Yuchao Zhang, Yuan Yuan, Qi Wang
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Graph Propagation Transformer for Graph Representation Learning
Zhe Chen, Hao Tan, Tao Wang, Tianrun Shen, Tong Lu, Qiuying Peng, Cheng Cheng, Yue Qi
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Graph Sampling-based Meta-Learning for Molecular Property Prediction
Xiang Zhuang, Qiang Zhang, Bin Wu, Keyan Ding, Yin Fang, Huajun Chen
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A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
Mehrdad khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K Reddy
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PPAT: Progressive Graph Pairwise Attention Network for Event Causality Identification
Zhenyu Liu, Baotian Hu, Zhenran Xu, Min Zhang
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Violin: Virtual Overbridge Linking for Enhancing Semi-supervised Learning on Graphs with Limited Labels
Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau
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Hierarchical Transformer for Scalable Graph Learning
Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma, Liang Wang
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Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation
Yalin Yu, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang
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Totally Dynamic Hypergraph Neural Networks
Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu
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Gapformer: Graph Transformer with Graph Pooling for Node Classification
Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu
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One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction
Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe
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Continuous-Time Graph Learning for Cascade Popularity Prediction
Xiaodong Lu, Shuo Ji, Le Yu, Leilei Sun, Bowen Du, Tongyu Zhu
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CSGCL: Community-Strength-Enhanced Graph Contrastive Learning
Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang
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Enabling Abductive Learning to Exploit Knowledge Graph
Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou
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CONGREGATE: Contrastive Graph Clustering in Curvature Spaces
Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu
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LGI-GT: Graph Transformers with Local and Global Operators Interleaving
Shuo Yin, Guoqiang Zhong
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An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations
Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse, Shajith Ikbal, Akihiro Kishimoto, Guilherme Lima, Ndivhuwo Makondo, Radu Marinescu
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MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
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LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity
Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao
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Globally Consistent Federated Graph Autoencoder for Non-IID Graphs
Kun Guo, Yutong Fang, Qingqing Huang, Yuting Liang, Ziyao Zhang, Wenyu He, Liu Yang, Kai Chen, Ximeng Liu, Wenzhong Guo
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SemiGNN-PPI: Self-Ensembling Multi-Graph Neural Network for Efficient and Generalizable Protein–Protein Interaction Prediction
Ziyuan Zhao, Peisheng Qian, Xulei Yang, Zeng Zeng, Cuntai Guan, Wai Leong Tam, Xiaoli Li
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Minimizing Reachability Times on Temporal Graphs via Shifting Labels
Argyrios Deligkas, Eduard Eiben, George Skretas
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Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification
Zheng Gong, Guifeng Wang, Ying Sun, Qi Liu, Yuting Ning, Hui Xiong, Jingyu Peng
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SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Sheng Tian, Jihai Dong, Jintang Li, WENLONG ZHAO, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
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Graph Neural Convection-Diffusion with Heterophily
KAI ZHAO, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay
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Semi-supervised Domain Adaptation in Graph Transfer Learning
Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong
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Multi-Scale Subgraph Contrastive Learning
Yanbei Liu, Yu Zhao, Xiao Wang, Lei Geng, Zhitao Xiao
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Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction
Luotao Liu, Feng Huang, Xuan Liu, Zhankun Xiong, Menglu Li, Congzhi Song, Wen Zhang
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Multi-View Robust Graph Representation Learning for Graph Classification
Guanghui Ma, Chunming Hu, Ling Ge, Hong Zhang
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Graph-based Semi-supervised Local Clustering with Few Labeled Nodes
Zhaiming Shen, Ming-Jun Lai, Sheng Li
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Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning
Hao Dong, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, Yanjie Fu
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FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks
Xinyu Fu, Irwin King
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Intent-aware Recommendation via Disentangled Graph Contrastive Learning
Yuling Wang, Xiao Wang, Xiangzhou Huang, Yanhua Yu, Haoyang Li, Mengdi Zhang, Zirui Guo, Wei Wu
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Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction
Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King
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Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
Hongjun Wang, Jiyuan Chen, Lun Du, Qiang Fu, Shi Han, Xuan Song
ICML-2023
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A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson
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A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
Yifan Chen, Rentian Yao, Yun Yang, Jie Chen
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Additive Causal Bandits with Unknown Graph
Alan Malek, Virginia Aglietti, Silvia Chiappa
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Alternately Optimized Graph Neural Networks
Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
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Boosting Graph Contrastive Learning via Graph Contrastive Saliency
Chunyu Wei, Yu Wang, Bing Bai, Kai Ni, David J. Brady, LU FANG
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ClusterFuG: Clustering Fully connected Graphs by Multicut
Ahmed Abbas, Paul Swoboda
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CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo
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Conditional Graph Information Bottleneck for Molecular Relational Learning
Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park
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D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching
Xuanzhou Liu, Lin Zhang, Jiaqi Sun, Yujiu Yang, Haiqin Yang
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DRew: Dynamically Rewired Message Passing with Delay
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
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Dink-Net: Neural Clustering on Large Graphs
Yue Liu, KE LIANG, Jun Xia, sihang zhou, Xihong Yang, Xinwang Liu, Stan Z. Li
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Disentangled Multiplex Graph Representation Learning
Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu
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Distribution Free Prediction Sets for Node Classification
Jase Clarkson
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Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks
Peng XU, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu
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ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
Siyuan Chen, Pratik Pramod Fegade, Tianqi Chen, Phillip Gibbons, Todd Mowry
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Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
Joonhyuk Yang, Dongpil Shin, Hye Won Chung
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Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang
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Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
Xiaohui Chen, Jiaxing He, Xu Han, Liping Liu
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Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
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Ewald-based Long-Range Message Passing for Molecular Graphs
Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann
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Exphormer: Sparse Transformers for Graphs
Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland, Ali Kemal Sinop
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Fast Online Node Labeling for Very Large Graphs
Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh
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Featured Graph Coarsening with Similarity Guarantees
Manoj Kumar, Anurag Sharma, Shashwat Saxena, Sandeep Kumar
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Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
YIZHEN ZHENG, He Zhang, Vincent Lee, Yu Zheng, Xiao Wang, Shirui Pan
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Fisher Information Embedding for Node and Graph Learning
Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt
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From Hypergraph Energy Functions to Hypergraph Neural Networks
Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
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From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou, Xiyuan Wang, Muhan Zhang
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GC-Flow: A Graph-Based Flow Network for Effective Clustering
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen
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GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang
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GREAD: Graph Neural Reaction-Diffusion Networks
Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho
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Generated Graph Detection
Yihan Ma, Zhikun Zhang, Ning Yu, Xinlei He, Michael Backes, Yun Shen, Yang Zhang
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Graph Contrastive Backdoor Attacks
Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu
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Graph Generative Model for Benchmarking Graph Neural Networks
Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov
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Graph Inductive Biases in Transformers without Message Passing
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim
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Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication
AJAY KUMAR JAISWAL, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang
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Graph Mixup with Soft Alignments
Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou
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Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
Ryoma Sato
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Graph Neural Networks with Learnable and Optimal Polynomial Bases
Yuhe Guo, Zhewei Wei
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Graph Neural Tangent Kernel: Convergence on Large Graphs
Sanjukta Krishnagopal, Luana Ruiz
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Graph Positional Encoding via Random Feature Propagation
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
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GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
Yuwen Li, Miao Xiong, Bryan Hooi
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HOPE: High-order Graph ODE For Modeling Interacting Dynamics
Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun
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Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L Dyer
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Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Minghao Guo, Veronika Thost, Samuel W Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik
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Implicit Graph Neural Networks: A Monotone Operator Viewpoint
Justin Baker, Qingsong Wang, Cory D Hauck, Bao Wang
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Improving Graph Generation by Restricting Graph Bandwidth
Nathaniel Lee Diamant, Alex Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia
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Improving Graph Neural Networks with Learnable Propagation Operators
Moshe Eliasof, Lars Ruthotto, Eran Treister
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InGram: Inductive Knowledge Graph Embedding via Relation Graphs
Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang
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LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu
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Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
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Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks
Feng Ji, See Hian Lee, Hanyang Meng, Kai Zhao, Jielong Yang, Wee Peng Tay
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Linkless Link Prediction via Relational Distillation
Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao
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Local Vertex Colouring Graph Neural Networks
Shouheng Li, Dongwoo Kim, Qing Wang
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Modeling Dynamic Environments with Scene Graph Memory
Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín
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Multi-class Graph Clustering via Approximated Effective
$p$ -ResistanceShota Saito, Mark Herbster
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Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks
Qiyu Kang, Kai Zhao, Yang Song, Sijie Wang, Wee Peng Tay
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On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
Richard A Watson, Hengrui Cai, Xinming An, Samuel McLean, Rui Song
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On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein
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On the Connection Between MPNN and Graph Transformer
Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang
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On the Expressive Power of Geometric Graph Neural Networks
Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lio
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One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding
Daniel Severo, James Townsend, Ashish J Khisti, Alireza Makhzani
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Online Learning with Feedback Graphs: The True Shape of Regret
Tomáš Kocák, Alexandra Carpentier
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PLay: Parametrically Conditioned Layout Generation using Latent Diffusion
Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li
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Path Neural Networks: Expressive and Accurate Graph Neural Networks
Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer, Michalis Vazirgiannis
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Personalized Subgraph Federated Learning
Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang
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Randomized Schur Complement Views for Graph Contrastive Learning
Vignesh Kothapalli
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Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
Saro Passaro, C. Lawrence Zitnick
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Relevant Walk Search for Explaining Graph Neural Networks
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller, Shinichi Nakajima
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Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching
Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li
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Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
Khang Nguyen, Nong Minh Hieu, Vinh Duc NGUYEN, Nhat Ho, Stanley Osher, Tan Minh Nguyen
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Rotation and Translation Invariant Representation Learning with Implicit Neural Representations
Sehyun Kwon, Joo Young Choi, Ernest K. Ryu
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SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning
Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu
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Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
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SlotGAT: Slot-based Message Passing for Heterogeneous Graphs
Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li
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Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming
Yufan Huang, C. Seshadhri, David F. Gleich
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Tight and fast generalization error bound of graph embedding in metric space
Atsushi Suzuki, Atsushi Nitanda, Taiji Suzuki, jing wang, Feng Tian, Kenji Yamanishi
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Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering
Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi
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Towards Deep Attention in Graph Neural Networks: Problems and Remedies
Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin
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Towards Robust Graph Incremental Learning on Evolving Graphs
Junwei Su, Difan Zou, Zijun Zhang, Chuan Wu
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Towards Understanding and Reducing Graph Structural Noise for GNNs
Mingze Dong, Yuval Kluger
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Transformers Meet Directed Graphs
Simon Geisler, Yujia Li, Daniel J Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
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Understanding Oversquashing in GNNs through the Lens of Effective Resistance
Mitchell Black, Zhengchao Wan, Amir Nayyeri, Yusu Wang
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Vertical Federated Graph Neural Network for Recommender System
Peihua Mai, Yan Pang
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WL meet VC
Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe
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Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks
Xu Chu, Yujie Jin, Xin Wang, Shanghang Zhang, Yasha Wang, Wenwu Zhu, Hong Mei
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Which Invariance Should We Transfer? A Causal Minimax Learning Approach
Mingzhou Liu, Xiangyu Zheng, Xinwei Sun, Fang Fang, Yizhou Wang
KDD-2023
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Kernel Ridge Regression-Based Graph Dataset Distillation
Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong
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Reducing Exposure to Harmful Content via Graph Rewiring
Corinna Coupette, Stefan Neumann, Aristides Gionis
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Community-based Dynamic Graph Learning for Popularity Prediction
Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong
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GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network
Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang
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Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective
Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng
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MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Jiaxing Zhang, Dongsheng Luo, Hua Wei
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Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-Scale Disentangled Representations
Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan
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What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
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Efficient and Effective Edge-Wise Graph Representation Learning
Hewen Wang, Renchi Yang, Keke Huang, Xiaokui Xiao
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Towards Graph-Level Anomaly Detection via Deep Evolutionary Mapping
Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng
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VQNE: Variational Quantum Network Embedding with Application to Network Alignment
Xinyu Ye, Ge Yan, Junchi Yan
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CARL-G: Clustering-Accelerated Representation Learning on Graphs
William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
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On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms
Fanchen Bu, Kijung Shin
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Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity
Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
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Localised Adaptive Spatial-Temporal Graph Neural Network
Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao
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PERT-GNN: Latency Prediction for Microservice-Based Cloud-Native Applications via Graph Neural Networks
Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau
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Causal Effect Estimation on Hierarchical Spatial Graph Data
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
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Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information
Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang
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On Structural Expressive Power of Graph Transformers
Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng
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MGNN: Graph Neural Networks Inspired by Distance Geometry Problem
Guanyu Cui, Zhewei Wei
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Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song
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Learning Strong Graph Neural Networks with Weak Information
Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan
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Clenshaw Graph Neural Networks
Yuhe Guo, Zhewei Wei
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All in One: Multi-Task Prompting for Graph Neural Networks
Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan
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Certified Edge Unlearning for Graph Neural Networks
Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang
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Augmenting Recurrent Graph Neural Networks with a Cache
Guixiang Ma, Vy A Vo, Theodore L. Willke, Nesreen K. Ahmed
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Narrow the Input Mismatch in Deep Graph Neural Network Distillation
Qiqi Zhou, Yanyan Shen, Lei Chen
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Sketch-Based Anomaly Detection in Streaming Graphs
Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip Yu, Bryan Hooi
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Knowledge Graph Reasoning over Entities and Numerical Values
Jiaxin Bai, Chen Luo, zheng li, Qingyu Yin, Bing Yin, Yangqiu Song
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Exploiting Relation-Aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning
Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park
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AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning
Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
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Context-Aware Event Forecasting via Graph Disentanglement
Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-seng Chua
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Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers
Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang
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GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
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Grace: Graph Self-Distillation and Completion to Mitigate Degree-Relatednesses
Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou
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GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai
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Classification of Edge-Dependent Labels of Nodes in Hypergraphs
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin
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Enhancing Graph Representations Learning with Decorrelated Propagation
Hua Liu, Wei Jin, Xiaorui Liu, Hui Liu
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Meta Graph Learning for Long-Tail Recommendation
Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang
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Graph Neural Bandits
Yunzhe Qi, Yikun Ban, Jingrui He
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E-commerce Search via Content Collaborative Graph Neural Network
Guipeng Xv, Chen Lin, Wanxian Guan, Jinping Gou, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng
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Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin
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Knowledge Graph Self-Supervised Rationalization for Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang
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On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang
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Incremental Causal Graph Learning for Online Root Cause Analysis
Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen
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Transferable Graph Structure Learning for Graph-Based Traffic Forecasting Across Cities
Yilun Jin, Kai Chen, Qiang Yang
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FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework
Raneen Younis, Zahra Ahmadi, Abdul Hakmeh, Marco Fisichella
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Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-Source Knowledge Graphs
Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu
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Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation
Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen
-
Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation
Shichao Pei, Ziyi Kou, Qiannan Zhang, Xiangliang Zhang
-
Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree
Delvin Ce Zhang, Rex Ying, Hady W. Lauw
-
PROSE: Graph Structure Learning via Progressive Strategy
Huizhao Wang, Yao Fu, Tao Yu, Linghui Hu, Weihao Jiang, Shiliang Pu
-
Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos
-
Task-Equivariant Graph Few-Shot Learning
Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park
-
GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning
Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li
-
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders
Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong
-
DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection
Jiaying Wu, Bryan Hooi
-
FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs
Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-seng Chua, Qing He
-
A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability
Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du
-
Financial Default Prediction via Motif-Preserving Graph Neural Network with Curriculum Learning
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
-
Towards Reliable Rare Category Analysis on Graphs via Individual Calibration
Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou
-
QTIAH-GNN: Quantity and Topology Imbalance-Aware Heterogeneous Graph Neural Network for Bankruptcy Prediction
Yucheng Liu, Zipeng Gao, Xiangyang Liu, Pengfei Luo, Yang Yang, Hui Xiong; The Hong Kong University of Science and Technology
-
Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling
Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong
-
Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems
Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang
-
Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest
Sang-Hong Kim, Ha-Myung Park
-
Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds
Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang
-
DyTed: Disentangled Representation Learning for Discrete-Time Dynamic Graph
Kaike Zhang, Qi Cao, Gaolin Fang, Xu Bingbing, Hongjian Zou, Huawei Shen, Xueqi Cheng
-
Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation
Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang
-
WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window
Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang
-
EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation
Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang
-
Using Motif Transitions for Temporal Graph Generation
Penghang Liu, Ahmet Erdem Sariyuce
-
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan
-
Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks
Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin
-
Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models
Kartik Sharma, Rakshit Trivedi, Rohit Sridhar, Srijan Kumar
-
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy
Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang
-
Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction
Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, LEI BAI, Yang Wang
-
Spatial Heterophily Aware Graph Neural Networks
Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong; The Hong Kong University of Science and Technology
-
Leveraging Relational Graph Neural Network for Transductive Model Ensemble
Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang
-
When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei CHEN, Yang Yang
-
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang
-
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann
-
Reconstructing Graph Diffusion History from a Single Snapshot
Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong
-
Generalizing Graph ODE for Learning Complex System Dynamics across Environments
Zijie Huang, Yizhou Sun, Wei Wang
-
B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning
Mengyue Liu, Yun Lin, Jun Liu, Bohao Liu, Qinghua Zheng, Jin Song Dong
-
Similarity Preserving Adversarial Graph Contrastive Learning
Yeonjun In, Kanghoon Yoon, Chanyoung Park
-
HomoGCL: Rethinking Homophily in Graph Contrastive Learning
Wen-Zhi Li, Chang-Dong Wang, Hui Xiong; The Hong Kong University of Science and Technology), Jian-Huang Lai
-
Contrastive Cross-scale Graph Knowledge Synergy
Yifei Zhang, Yankai Chen, Zixing Song, Irwin King
-
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai
-
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs
Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang
-
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing
Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu
-
Semi-Supervised Graph Imbalanced Regression
Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang
-
Learning Joint Relational Co-Evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao
-
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection
Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li
-
Commonsense Knowledge Graph towards Supper APP and Its Applications in Alipay
Xiaoling Zang, Binbin Hu, Chu Jun, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong
-
Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering
Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, Lei Chen; Hong Kong University of Science and Technology
-
DGI: An Easy and Efficient Framework for GNN Model Evaluation
Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang
-
Learning Multivariate Hawkes Process via Graph Recurrent Neural Network
Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park
-
HUGE: Huge Unsupervised Graph Embeddings with TPUs
Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi
-
Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs
Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan
-
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research
Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu
-
MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification
Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen
-
Graph Learning in Physical-Informed Mesh-Reduced Space for Real-World Dynamic Systems
Yeping Hu, Bo Lei, Victor M. Castillo
-
Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs
Tingyan Xiang, Ao Li, Yugang Ji, Dong Li
-
TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation
Wenxin Tai, Bin Chen, Fan Zhou, Ting Zhong, Goce Trajcevski, Yong Wang, Kai Chen
-
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
Xinyue Hu, Lin Gu, Qiyuan An, Zhang Mengliang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu
-
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang
-
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications
Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
-
PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation
Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu
-
Adaptive Graph Contrastive Learning for Recommendation
Yangqin Jiang, Chao Huang, Lianghao Xia
-
Real Time Index and Search Across Large Quantities of GNN Experts For Low Latency Online Learning
Johan Zhi Kang Kok, Sien Yi Tan, Bingsheng He, Zhen Zhang
-
ILRoute: A Graph-based Imitation Learning Method to Unveil Riders’ Routing Strategies in Food Delivery Service
Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li
-
Deep Transfer Learning for City-Scale Cellular Traffic Generation through Urban Knowledge Graph
Zhang Shiyuan, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li
SIGIR-2023
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Adaptive Graph Representation Learning for Next POI Recommendation
Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li, Jiadi Yu
-
Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering
Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang
-
Candidate–aware Graph Contrastive Learning for Recommendation
Wei He, Guohao Sun, Jinhu Lu, Xiu Susie Fang
-
Continual Learning on Dynamic Graphs via Parameter Isolation
Peiyan Zhang, Yuchen Yan, Chaozhuo Li, Senzhang Wang, Xing Xie, Guojie Song, Sunghun Kim
-
Contrastive Learning for Signed Bipartite Graphs
Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, Yifei Wang
-
Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition
Jingyun Xu, Yi Cai
-
Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation
Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang, Chenghu Zhou
-
DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao
-
Dynamic Graph Evolution Learning for Recommendation
Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li
-
Generative-Contrastive Graph Learning for Recommendation
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
-
Graph Masked Autoencoder for Sequential Recommendation
Yaowen Ye, Lianghao Xia, Chao Huang
-
Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation
Qian Chen, Zhiqiang Guo, Jianjun Li, Guohui Li
-
Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu
-
LightGT: A Light Graph Transformer for Multimedia Recommendation
Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie, Tat-Seng Chua
-
M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation
Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li, Wei Wu
-
Graph Transformer for Recommendation
Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang
-
Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation
Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong
-
Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector Space
Wei Tang, Haifeng Sun, Jingyu Wang, Qi Qi, Jing Wang, Hao Yang, Shimin Tao
-
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu
-
Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network
Ran Li, Liang Zhang, Guannan Liu, Junjie Wu
-
Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Linhao Luo, Reza Haffari, Yuan Fang Li, Shirui Pan
-
Relation-Aware Multi-Positive Contrastive Knowledge Graph Completion with Embedding Dimension Scaling
Bin Shang, Yinliang Zhao, Di Wang, Jun Liu
-
Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction
Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen
-
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong
-
Session Search with Pre-trained Graph Classification Model
Shengjie Ma, Chong Chen, Jiaxin Mao, Qi Tian, Xuhui Jiang
-
Spatio-Temporal Hypergraph Learning for Next POI Recommendation
Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li, Wei Chu
-
StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios
Jiasheng Zhang, Jie Shao, Bin Cui
-
Subgraph Search over Neural-Symbolic Graphs
Ye Yuan, Delong Ma, Anbiao Wu, Jianbin Qin
-
Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis
Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang
-
Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs
Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin, Enhong Chen
-
Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation
Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang
-
Weighted Knowledge Graph Embedding
Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu
-
DeviceGPT: A Generative Pre-Training Transformer on the Heterogenous Graph for Internet of Things
Yimo Ren, Jinfa Wang, Hong Li, Hongsong Zhu, Limin Sun
-
DocGraphLM: Documental graph language model for information extraction
Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh, Kang Gu, Sameena Shah
-
Gated Attention with Asymmetric Regularization for Transformer-based Continual Graph Learning
Hongxiang Lin, Ruiqi Jia, Xiaoqing Lyu
-
Graph Collaborative Signals Denoising and Augmentation for Recommendation
Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu
-
Hierarchical Type Enhanced Negative Sampling for Knowledge Graph Embedding
Zhenzhou Lin, Zishuo Zhao, Jingyou Xie, Ying Shen
-
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraphs
Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
-
MDKG: Graph-Based Medical Knowledge-Guided Dialogue Generation
Usman Naseem, Surendrabikram Thapa, Qi Zhang, Liang Hu, Mehwish Nasim
-
Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion
Donghan Yu, Yiming Yang
-
Sharpness-Aware Graph Collaborative Filtering
Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das, Hao Yang
-
TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks
Min-Jeong Kim, Yeon-Chang Lee, Sang-Wook Kim
-
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
-
WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering
Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King
AAAI-2023
-
Self-Supervised Graph Learning for Long-Tailed Cognitive Diagnosis
Shanshan Wang, Zhen Zeng, Xun Yang, Xingyi Zhang
-
Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels
Zheyun Qin, Xiankai Lu, Xiushan Nie, Yilong Yin, Jianbing Shen
-
Asynchronous Event Processing with Local-Shift Graph Convolutional Network
Linhui Sun, Yifan Zhang, Jian Cheng, Hanqing Lu
-
Multi-Modal Knowledge Hypergraph for Diverse Image Retrieval
Yawen Zeng, Qin Jin, Tengfei Bao, Wenfeng Li
-
MulGT: Multi-Task Graph-Transformer with Task-Aware Knowledge Injection and Domain Knowledge-Driven Pooling for Whole Slide Image Analysis
Weiqin Zhao, Shujun Wang, Maximus Yeung, Tianye Niu, Lequan Yu
-
Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs
Erel Cohen, Omer Lev, Roie Zivan
-
Enhanced Multi-Relationships Integration Graph Convolutional Network for Inferring Substitutable and Complementary Items
Huajie Chen, Jiyuan He, Weisheng Xu, Tao Feng, Ming Liu, Tianyu Song, Runfeng Yao, Yuanyuan Qiao
-
Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding
Mingyang Chen, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan, Huajun Chen
-
Dual Low-Rank Graph Autoencoder for Semantic and Topological Networks
Zhaoliang Chen, Zhihao Wu, Shiping Wang, Wenzhong Guo
-
Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction
Chanyoung Chung, Joyce Jiyoung Whang
-
Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs
Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu
-
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang
-
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning
Xumeng Gong, Cheng Yang, Chuan Shi
-
Generic and Dynamic Graph Representation Learning for Crowd Flow Modeling
Liangzhe Han, Ruixing Zhang, Leilei Sun, Bowen Du, Yanjie Fu, Tongyu Zhu
-
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
Han Huang, Leilei Sun, Bowen Du, Weifeng Lv
-
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation
Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu
-
Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye
-
GLCC: A General Framework for Graph-Level Clustering
Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang
-
Signed Laplacian Graph Neural Networks
Yu Li, Meng Qu, Jian Tang, Yi Chang
-
Scalable and Effective Conductance-Based Graph Clustering
Longlong Lin, Ronghua Li, Tao Jia
-
Multi-Domain Generalized Graph Meta Learning
Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Guohao Li, Sanglu Lu
-
IterDE: An Iterative Knowledge Distillation Framework for Knowledge Graph Embeddings
Jiajun Liu, Peng Wang, Ziyu Shang, Chenxiao Wu
-
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan
-
On Generalized Degree Fairness in Graph Neural Networks
Zemin Liu, Trung-Kien Nguyen, Yuan Fang
-
Graph Structure Learning on User Mobility Data for Social Relationship Inference
Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong
-
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces
Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu
-
Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information
Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu
-
Easy Begun Is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout
Hongjun Wang, Jiyuan Chen, Tong Pan, Zipei Fan, Xuan Song, Renhe Jiang, Lingyu Zhang, Yi Xie, Zhongyi Wang, Boyuan Zhang
-
Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment
Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie
-
Beyond Graph Convolutional Network: An Interpretable Regularizer-Centered Optimization Framework
Shiping Wang, Zhihao Wu, Yuhong Chen, Yong Chen
-
Augmenting Affective Dependency Graph via Iterative Incongruity Graph Learning for Sarcasm Detection
Xiaobao Wang, Yiqi Dong, Di Jin, Yawen Li, Longbiao Wang, Jianwu Dang
-
Temporal Knowledge Graph Reasoning with Historical Contrastive Learning
Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu
-
Next POI Recommendation with Dynamic Graph and Explicit Dependency
Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han
-
Learning to Count Isomorphisms with Graph Neural Networks
Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
-
Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator
Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang
-
Deep Graph Structural Infomax
Wenting Zhao, Gongping Xu, Zhen Cui, Siqiang Luo, Cheng Long, Tong Zhang
-
A Provable Framework of Learning Graph Embeddings via Summarization
Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng
-
GraphSR: A Data Augmentation Algorithm for Imbalanced Node Classification
Mengting Zhou, Zhiguo Gong
-
GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM
Silin Zhou, Jing Li, Hao Wang, Shuo Shang, Peng Han
-
Heterogeneous Graph Learning for Multi-Modal Medical Data Analysis
Sein Kim, Namkyeong Lee, Junseok Lee, Dongmin Hyun, Chanyoung Park
-
GRIP: Graph Representation of Immune Repertoire Using Graph Neural Network and Transformer
Yongju Lee, Hyunho Lee, Kyoungseob Shin, Sunghoon Kwon
-
Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs
Fang Wu, Dragomir Radev, Stan Z. Li
-
Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction
Zhankun Xiong, Shichao Liu, Feng Huang, Ziyan Wang, Xuan Liu, Zhongfei Zhang, Wen Zhang
-
Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs
Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen
-
DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing
Haoran Luo, Haihong E, Ling Tan, Gengxian Zhou, Tianyu Yao, Kaiyang Wan
-
Generalizing Downsampling from Regular Data to Graphs
Davide Bacciu, Alessio Conte, Francesco Landolfi
-
Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Toyotaro Suzumura, Manish Singh
-
FTM: A Frame-Level Timeline Modeling Method for Temporal Graph Representation Learning
Bowen Cao, Qichen Ye, Weiyuan Xu, Yuexian Zou
-
Where Will Players Move Next? Dynamic Graphs and Hierarchical Fusion for Movement Forecasting in Badminton
Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng
-
Graph Ordering Attention Networks
Michail Chatzianastasis, Johannes Lutzeyer, George Dasoulas, Michalis Vazirgiannis
-
Attribute and Structure Preserving Graph Contrastive Learning
Jialu Chen, Gang Kou
-
Context-Aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding
Qianyu Chen, Xin Li, Kunnan Geng, Mingzhong Wang
-
Topological Pooling on Graphs
Yuzhou Chen, Yulia R. Gel
-
Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning
Jiashun Cheng, Man Li, Jia Li, Fugee Tsung
-
Scalable Spatiotemporal Graph Neural Networks
Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi
-
CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials
Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
-
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning
Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu
-
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
-
Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View
Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu, Hu Jin, Yue Liu, Zhibin Dong
-
Directed Acyclic Graph Structure Learning from Dynamic Graphs
Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi
-
Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees
Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai
-
Scalable Attributed-Graph Subspace Clustering
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
-
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li
-
Interpolating Graph Pair to Regularize Graph Classification
Hongyu Guo, Yongyi Mao
-
Graph Knows Unknowns: Reformulate Zero-Shot Learning as Sample-Level Graph Recognition
Jingcai Guo, Song Guo, Qihua Zhou, Ziming Liu, Xiaocheng Lu, Fushuo Huo
-
Self-Supervised Bidirectional Learning for Graph Matching
Wenqi Guo, Lin Zhang, Shikui Tu, Lei Xu
-
Boosting Graph Neural Networks via Adaptive Knowledge Distillation
Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla
-
Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis
Thi Kieu Khanh Ho, Narges Armanfard
-
Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering
Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He
-
Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning
Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin
-
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura
-
Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu
-
Local-Global Defense against Unsupervised Adversarial Attacks on Graphs
Di Jin, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei, Zhen Wang
-
Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
-
LoNe Sampler: Graph Node Embeddings by Coordinated Local Neighborhood Sampling
Konstantin Kutzkov
-
I’m Me, We’re Us, and I’m Us: Tri-directional Contrastive Learning on Hypergraphs
Dongjin Lee, Kijung Shin
-
Time-Aware Random Walk Diffusion to Improve Dynamic Graph Learning
Jong-whi Lee, Jinhong Jung
-
Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks
Chao Li, Hao Xu, Kun He
-
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
-
Restructuring Graph for Higher Homophily via Adaptive Spectral Clustering
Shouheng Li, Dongwoo Kim, Qing Wang
-
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network
Tong Li, Jiale Deng, Yanyan Shen, Luyu Qiu, Huang Yongxiang, Caleb Chen Cao
-
Dual Label-Guided Graph Refinement for Multi-View Graph Clustering
Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He
-
Hard Sample Aware Network for Contrastive Deep Graph Clustering
Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen
-
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach
Sérgio Machado, Anirudh Sridhar, Paulo Gil, Jorge Henriques, José M. F. Moura, Augusto Santos
-
Boundary Graph Neural Networks for 3D Simulations
Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
-
Multiplex Graph Representation Learning via Common and Private Information Mining
Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu
-
Inferring Patient Zero on Temporal Networks via Graph Neural Networks
Xiaolei Ru, Jack Murdoch Moore, Xin-Ya Zhang, Yeting Zeng, Gang Yan
-
Neighbor Contrastive Learning on Learnable Graph Augmentation
Xiao Shen, Dewang Sun, Shirui Pan, Xi Zhou, Laurence T. Yang
-
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang
-
Metric Multi-View Graph Clustering
Yuze Tan, Yixi Liu, Hongjie Wu, Jiancheng Lv, Shudong Huang
-
Heterogeneous Graph Masked Autoencoders
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla
-
USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network
Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, Jiamou Liu
-
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability
Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang
-
Non-IID Transfer Learning on Graphs
Jun Wu, Jingrui He, Elizabeth Ainsworth
-
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework
Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li
-
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks
Yihan Wu, Aleksandar Bojchevski, Heng Huang
-
GraphPrompt: Graph-Based Prompt Templates for Biomedical Synonym Prediction
Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang
-
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis
Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Liò
-
Reinforcement Causal Structure Learning on Order Graph
Dezhi Yang, Guoxian Yu, Jun Wang, Zhengtian Wu, Maozu Guo
-
Simple and Efficient Heterogeneous Graph Neural Network
Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye, Dongrui Fan
-
Cluster-Guided Contrastive Graph Clustering Network
Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, En Zhu
-
Lifelong Compression Mixture Model via Knowledge Relationship Graph
Fei Ye, Adrian G. Bors
-
Random Walk Conformer: Learning Graph Representation from Long and Short Range
Pei-Kai Yeh, Hsi-Wen Chen, Ming-Syan Chen
-
Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering
Jiali You, Zhenwen Ren, Xiaojian You, Haoran Li, Yuancheng Yao
-
Substructure Aware Graph Neural Networks
DingYi Zeng, Wanlong Liu, Wenyu Chen, Li Zhou, Malu Zhang, Hong Qu
-
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li
-
DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks
Lei Zhang, Xiaodong Yan, Jianshan He, Ruopeng Li, Wei Chu
-
Let the Data Choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-View Clustering
Pei Zhang, Siwei Wang, Liang Li, Changwang Zhang, Xinwang Liu, En Zhu, Zhe Liu, Lu Zhou, Lei Luo
-
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond
Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King
-
Dynamic Heterogeneous Graph Attention Neural Architecture Search
Zeyang Zhang, Ziwei Zhang, Xin Wang, Yijian Qin, Zhou Qin, Wenwu Zhu
-
Tensorized Incomplete Multi-View Clustering with Intrinsic Graph Completion
Shuping Zhao, Jie Wen, Lunke Fei, Bob Zhang
-
Data Imputation with Iterative Graph Reconstruction
Jiajun Zhong, Ning Gui, Weiwei Ye
-
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical Models
Jonathan Feldstein, Dominic Phillips, Efthymia Tsamoura
-
Fair Short Paths in Vertex-Colored Graphs
Matthias Bentert, Leon Kellerhals, Rolf Niedermeier
-
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks
Angelina Brilliantova, Hannah Miller, Ivona Bezáková
-
Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction
Bo Li, Wei Ye, Jinglei Zhang, Shikun Zhang
-
Graph Component Contrastive Learning for Concept Relatedness Estimation
Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, Irwin King
-
Improving Interpretability via Explicit Word Interaction Graph Layer
Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi
-
Exploring Faithful Rationale for Multi-Hop Fact Verification via Salience-Aware Graph Learning
Jiasheng Si, Yingjie Zhu, Deyu Zhou
-
Continual Graph Convolutional Network for Text Classification
Tiandeng Wu, Qijiong Liu, Yi Cao, Yao Huang, Xiao-Ming Wu, Jiandong Ding
-
Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection
Tao Yang, Jinghao Deng, Xiaojun Quan, Qifan Wang
ICLR-2023
-
Towards Open Temporal Graph Neural Networks
Kaituo Feng, Changsheng Li, Xiaolu Zhang, JUN ZHOU
-
AutoGT: Automated Graph Transformer Architecture Search
Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li, Wenwu Zhu
-
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Bohang Zhang, Shengjie Luo, Liwei Wang, Di He
-
Graph Neural Networks for Link Prediction with Subgraph Sketching
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire
-
Do We Really Need Complicated Model Architectures For Temporal Networks?
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
-
Learning on Large-scale Text-attributed Graphs via Variational Inference
Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang
-
Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks
Guangji Bai, Chen Ling, Liang Zhao
-
Learning Fair Graph Representations via Automated Data Augmentations
Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou
-
Spectral Augmentation for Self-Supervised Learning on Graphs
Lu Lin, Jinghui Chen, Hongning Wang
-
Serving Graph Compression for Graph Neural Networks
Si Si, Felix Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
-
Effects of Graph Convolutions in Multi-layer Networks
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
-
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren
-
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
Cameron Diao, Ricky Loynd
-
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Yi-Lun Liao, Tess Smidt
-
Learning rigid dynamics with face interaction graph networks
Kelsey R Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William F Whitney, Alvaro Sanchez-Gonzalez, Peter Battaglia, Tobias Pfaff
-
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
Cameron Diao, Ricky Loynd
-
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
-
ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
Aleksandar Pavlović, Emanuel Sallinger
-
Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla
-
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
-
On Representing Linear Programs by Graph Neural Networks
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
-
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin
-
MeshDiffusion: Score-based Generative 3D Mesh Modeling
Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu
-
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
Zhihao Shi, Xize Liang, Jie Wang
-
Learning Controllable Adaptive Simulation for Multi-resolution Physics
Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec
-
Automated Data Augmentations for Graph Classification
Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
-
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang
-
Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective
Kuan Li, Yang Liu, Xiang Ao, Qing He
-
Agent-based Graph Neural Networks
Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer
-
Characterizing the Influence of Graph Elements
Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong
-
Limitless Stability for Graph Convolutional Networks
Christian Koke
-
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
Jinsong Chen, Kaiyuan Gao, Gaichao Li, Kun He
-
Empowering Graph Representation Learning with Test-Time Graph Transformation
Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
-
N-WL: A New Hierarchy of Expressivity for Graph Neural Networks
Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, Muhammad Farhan
-
Are More Layers Beneficial to Graph Transformers?
Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei
-
Strategic Classification with Graph Neural Networks
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
-
Robust Graph Dictionary Learning
Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian
-
Specformer: Spectral Graph Neural Networks Meet Transformers
Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao
-
DiGress: Discrete Denoising diffusion for graph generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard
-
LogicDP: Creating Labels for Graph Data via Inductive Logic Programming
Yuan Yang, Faramarz Fekri, James Clayton Kerce, Ali Payani
-
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
Zehao Niu, Mihai Anitescu, Jie Chen
-
Explaining Temporal Graph Models through an Explorer-Navigator Framework
Wenwen Xia, Mincai Lai, Caihua Shan, Yao Zhang, Xinnan Dai, Xiang Li, Dongsheng Li
-
Learning Symbolic Models for Graph-structured Physical Mechanism
Hongzhi Shi, Jingtao Ding, Yufan Cao, quanming yao, Li Liu, Yong Li
-
Efficient Model Updates for Approximate Unlearning of Graph-Structured Data
Eli Chien, Chao Pan, Olgica Milenkovic
-
Imitating Graph-Based Planning with Goal-Conditioned Policies
Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin
-
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
Namyong Park, Ryan A. Rossi, Nesreen Ahmed, Christos Faloutsos
-
On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang
-
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang
-
Grounding Graph Network Simulators using Physical Sensor Observations
Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann
-
Graph Contrastive Learning for Skeleton-based Action Recognition
Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng
-
A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps
Kiarash Jamali, Dari Kimanius, Sjors HW Scheres
-
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan
-
Rethinking Graph Lottery Tickets: Graph Sparsity Matters
Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku
-
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems
Suresh Bishnoi, Ravinder Bhattoo, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan
-
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Seungwoong Ha, Hawoong Jeong
-
GReTo: Remedying dynamic graph topology-task discordance via target homophily
Zhengyang Zhou, qihe huang, Gengyu Lin, Kuo Yang, LEI BAI, Yang Wang
-
Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
Cheng Zhang
-
Unveiling the sampling density in non-uniform geometric graphs
Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie
-
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
-
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li
-
Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez, Xiao Liu, Alison Q O'Neil, Sotirios A. Tsaftaris
-
Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning
Deyao Zhu, Li Erran Li, Mohamed Elhoseiny
-
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montufar
-
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
-
Revisiting Robustness in Graph Machine Learning
Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann
-
Learnable Graph Convolutional Attention Networks
Adrián Javaloy, Pablo Sanchez Martin, Amit Levi, Isabel Valera
-
Matching receptor to odorant with protein language and graph neural networks
Matej Hladiš, Maxence Lalis, Sebastien Fiorucci, Jérémie Topin
-
Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson
-
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova
-
Fair Attribute Completion on Graph with Missing Attributes
Dongliang Guo, Zhixuan Chu, Sheng Li
-
Multimodal Analogical Reasoning over Knowledge Graphs
Ningyu Zhang, Lei Li, Xiang Chen, Xiaozhuan Liang, Shumin Deng, Huajun Chen
-
Global Explainability of GNNs via Logic Combination of Learned Concepts
Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Lio, Andrea Passerini
-
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
-
A2Q: Aggregation-Aware Quantization for Graph Neural Networks
Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng
-
Graph Domain Adaptation via Theory-Grounded Spectral Regularization
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
-
Learning Hierarchical Protein Representations via Complete 3D Graph Networks
Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji
-
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States
Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin
-
Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation
Yun Young Choi, Sun Woo Park, Youngho Woo, U Jin Choi
-
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie
-
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
Alessio Gravina, Davide Bacciu, Claudio Gallicchio
-
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
Xiaoqi Wang, Han Wei Shen
-
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
Bowen Jin, Yu Zhang, Yu Meng, Jiawei Han
-
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron N Musco
-
Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning
Hong-Yu Zhou, Yunxiang Fu, Zhicheng Zhang, Bian Cheng, Yizhou Yu
-
Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems
Zhongyuan Zhao, Ananthram Swami, Santiago Segarra
-
Anisotropic Message Passing: Graph Neural Networks with Directional and Long-Range Interactions
Moritz Thürlemann, Sereina Riniker
-
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang
-
Confidence-Based Feature Imputation for Graphs with Partially Known Features
Daeho Um, Jiwoong Park, Seulki Park, Jin young Choi
-
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves
-
Neural Compositional Rule Learning for Knowledge Graph Reasoning
Kewei Cheng, Nesreen Ahmed, Yizhou Sun
-
DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
Wenqian Li, Yinchuan Li, Zhigang Li, Jianye HAO, Yan Pang
-
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
-
UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph
Jinhao Jiang, Kun Zhou, Xin Zhao, Ji-Rong Wen
-
Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs
Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang
-
AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec
-
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan
-
Subsampling in Large Graphs Using Ricci Curvature
Shushan Wu, Huimin Cheng, Jiazhang Cai, Ping Ma, Wenxuan Zhong
-
Spacetime Representation Learning
Marc T. Law, James Lucas
-
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji
-
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
-
A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
-
A Differential Geometric View and Explainability of GNN on Evolving Graphs
Yazheng Liu, Xi Zhang, Sihong Xie
-
Link Prediction with Non-Contrastive Learning
William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah
-
Learning to Induce Causal Structure
Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
-
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing
Yunchong Song, Chenghu Zhou, Xinbing Wang, Zhouhan Lin
-
Logical Message Passing Networks with One-hop Inference on Atomic Formulas
Zihao Wang, Yangqiu Song, Ginny Wong, Simon See
-
Fundamental Limits in Formal Verification of Message-Passing Neural Networks
Marco Sälzer, Martin Lange
-
Robust Scheduling with GFlowNets
David W Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan
-
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
-
O-GNN: incorporating ring priors into molecular modeling
Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
-
Molecule Generation For Target Protein Binding with Structural Motifs
ZAIXI ZHANG, Yaosen Min, Shuxin Zheng, Qi Liu
-
A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming
Qingyu Han, Linxin Yang, Qian Chen, Xiang Zhou, Dong Zhang, Akang Wang, Ruoyu Sun, Xiaodong Luo
-
Label Propagation with Weak Supervision
Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan
-
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond
Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang
-
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola
-
On Explaining Neural Network Robustness with Activation Path
Ziping Jiang
-
Equivariant Hypergraph Diffusion Neural Operators
Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
-
Interpretable Geometric Deep Learning via Learnable Randomness Injection
Siqi Miao, Yunan Luo, Mia Liu, Pan Li
-
Protein Representation Learning by Geometric Structure Pretraining
Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang
-
Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction
Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, Kuk-Jin Yoon
-
TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce
-
Boosting Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang, Tat-Seng Chua
WSDM-2023
-
BLADE: Biased Neighborhood Sampling based Graph Neural Network for Directed Graphs
Srinivas Virinchi, Anoop Saladi
-
Simplifying Graph-based Collaborative Filtering for Recommendation
Li He, Xianzhi Wang, Dingxian Wang, Haoyuan Zou, Hongzhi Yin, Guandong Xu
-
Self-Supervised Group Graph Collaborative Filtering for Group Recommendation
Kang Li, Chang-Dong Wang, Jian-Huang Lai, Huaqiang Yuan
-
Minimum Entropy Principle Guided Graph Neural Networks
Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su
-
Learning to Distill Graph Neural Networks
Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin
-
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, Dongmei Zhang
-
Global Counterfactual Explainer for Graph Neural Networks
Zexi Huang, Mert Kosan, Sourav Medya, Sayan Ranu, Ambuj K. Singh
-
Effective Graph Kernels for Evolving Functional Brain Networks
Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu
-
Self-Supervised Graph Structure Refinement for Graph Neural Networks
Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye
-
Learning Stance Embeddings from Signed Social Graphs
John Pougué-Biyong, Akshay Gupta, Aria Haghighi, Ahmed El-Kishky
-
Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren
-
A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework
Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang
-
Simultaneous Linear Multi-view Attributed Graph Representation Learning and Clustering
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
-
Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs
Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang
-
Self-supervised Graph Representation Learning for Black Market Account Detection
Zequan Xu, Lianyun Li, Hui Li, Qihang Sun, Shaofeng Hu, Rongrong Ji
-
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan
-
Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
-
Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation
Qingyu Bing, Qiannan Zhu, Zhicheng Dou
-
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang
-
VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu, Han Xu
-
Heterogeneous Graph Contrastive Learning for Recommendation
Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo
-
SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation
Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen
-
Robust Training of Graph Neural Networks via Noise Governance
Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu
-
Cooperative Explanations of Graph Neural Networks
Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua
-
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection
Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
-
Towards Faithful and Consistent Explanations for Graph Neural Networks
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
-
Position-Aware Subgraph Neural Networks with Data-Efficient Learning
Chang Liu, Yuwen Yang, Zhe Xie, Hongtao Lu, Yue Ding
-
Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution
Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang
-
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang
-
Inductive Graph Transformer for Delivery Time Estimation
Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung
-
Search Behavior Prediction: A Hypergraph Perspective
Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian
-
Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao
-
Heterogeneous Graph-based Context-aware Document Ranking
Shuting Wang, Zhicheng Dou, Yutao Zhu
-
Graph Summarization via Node Grouping: A Spectral Algorithm
Arpit Merchant, Michael Mathioudakis, Yanhao Wang
-
Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph
Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu
-
Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs
Linhao Luo, Gholamreza Haffari, Shirui Pan
-
S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking
Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu
-
Combining vs. Transferring Knowledge: Investigating Strategies for Improving Demographic Inference in Low Resource Settings
Yaguang Liu, Lisa Singh
-
Active Ensemble Learning for Knowledge Graph Error Detection
Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, Zihao Zhao
-
Stochastic Solutions for Dense Subgraph Discovery in Multilayer Networks
Yasushi Kawase, Atsushi Miyauchi, Hanna Sumita
-
Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval
Taiqiang Wu, Xingyu Bai, Weigang Guo, Weijie Liu, Siheng Li, Yujiu Yang
-
Web of Conferences: A Conference Knowledge Graph
Shuo Yu, Ciyuan Peng, Chengchuan Xu, Chen Zhang, Feng Xia
-
Developing and Evaluating Graph Counterfactual Explanation with GRETEL
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
-
Generalizing Graph Neural Network across Graphs and Time
Zhihao Wen
-
Graphs: Privacy and Generation through ML
Rucha Bhalchandra Joshi
-
Data-Efficient Graph Learning Meets Ethical Challenges
Tao Tang
-
From Classic GNNs to Hyper-GNNs for Detecting Camouflaged Malicious Actors
Venus Haghighi
-
Efficient Graph Learning for Anomaly Detection Systems
Falih Gozi Febrinanto
WWW-2023
-
GELTOR: A Graph Embedding Method based on Listwise Learning to Rank
Masoud Reyhani Hamedani, Jin-Su Ryu, Sang-Wook Kim
-
Graph-less Collaborative Filtering
Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu
-
Fair Graph Representation Learning via Diverse Mixture-of-Experts
Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang
-
Multi-Aspect Heterogeneous Graph Augmentation
Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu, Weiqiang Wang
-
RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks
Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao, Zijian Zhang
-
Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr
-
Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network
Zhilun Zhou, Yu Liu, Jingtao Ding, Depeng Jin, Yong Li
-
SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
-
Graph Self-supervised Learning with Augmentation-aware Contrastive Learning
Dong Chen, Xiang Zhao, Wei Wang, Zhen Tan, Weidong Xiao
-
Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation
Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, Haoming Lyu
-
Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters
Liangtian Wan, Xiaona Li, Huijin Han, Xiaoran Yan, Lu Sun, Zhaolong Ning, Feng Xia
-
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds
Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren
-
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks
Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang
-
An Attentional Multi-scale Co-evolving Model for Dynamic Link Prediction
Guozhen Zhang, Tian Ye, Depeng Jin, Yong Li
-
Robust Graph Representation Learning for Local Corruption Recovery
Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang
-
Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation
Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng, Yang Yao
-
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification
Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li
-
Graph Neural Networks without Propagation
Liang Yang, Qiuliang Zhang, Runjie Shi, Wenmiao Zhou, Bingxin Niu, Chuan Wang, Xiaochun Cao, Dongxiao He, Zhen Wang, Yuanfang Guo
-
TIGER: Temporal Interaction Graph Embedding with Restarts
Yao Zhang, Yun Xiong, Yongxiang Liao, Yiheng Sun, Yucheng Jin, Xuehao Zheng, Yangyong Zhu
-
Self-Supervised Teaching and Learning of Representations on Graphs
Liangtian Wan, Zhenqiang Fu, Lu Sun, Xianpeng Wang, Gang Xu, Xiaoran Yan, Feng Xia
-
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization
Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu
-
Homophily-oriented Heterogeneous Graph Rewiring
Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang
-
HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction
Qijie Bai, Changli Nie, Haiwei Zhang, Dongming Zhao, Xiaojie Yuan
-
Rethinking Structural Encodings: Adaptive Graph Transformer for Node Classification Task
Xiaojun Ma, Qin Chen, Yi Wu, Guojie Song, Liang Wang, Bo Zheng
-
CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion
Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen
-
Federated Node Classification over Graphs with Latent Link-type Heterogeneity
Han Xie, Li Xiong, Carl Yang
-
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs
Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li
-
Semi-Supervised Embedding of Attributed Multiplex Networks
Ylli Sadikaj, Justus Rass, Yllka Velaj, Claudia Plant
-
Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification
Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao
-
HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer
Qiheng Mao, Zemin Liu, Chenghao Liu, Jianling Sun
-
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs
Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan
-
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning
Haoran Yang, Hongxu Chen, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu
-
Minimum Topology Attacks for Graph Neural Networks
Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du
-
Multi-head Variational Graph Autoencoder Constrained by Sum-product Networks
Riting Xia, Yan Zhang, Chunxu Zhang, Xueyan Liu, Bo Yang
-
GIF: A General Graph Unlearning Strategy via Influence Function
Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He
-
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen, Longbiao Chen
-
Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation
Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan
-
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
-
Unlearning Graph Classifiers with Limited Data Resources
Chao Pan, Eli Chien, Olgica Milenkovic
-
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks
Zhizhi Yu, Di Jin, Cuiying Huo, Zhiqiang Wang, Xiulong Liu, Heng Qi, Jia Wu, Lingfei Wu
-
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner
Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang
-
CogDL: A Comprehensive Library for Graph Deep Learning
Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang
-
ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation
Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang
-
Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model
Xiaoyu You, Chi Li, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan, Min Yang
-
Compressed Interaction Graph based Framework for Multi-behavior Recommendation
Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang
-
Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation
Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang, Bo Zheng
-
Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li
-
Multi-Behavior Recommendation with Cascading Graph Convolution Networks
Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao, Yuxin Peng
-
Personalized Graph Signal Processing for Collaborative Filtering
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu
-
Dynamically Expandable Graph Convolution for Streaming Recommendation
Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma
-
Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systems
Heesoo Jung, Sangpil Kim, Hogun Park
-
Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum
Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
-
Node-wise Diffusion for Scalable Graph Learning
Keke Huang, Jing Tang, Juncheng Liu, Renchi Yang, Xiaokui Xiao
-
CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
-
MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding
Xiaoyu You, Beina Sheng, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Fuli Feng
-
Curriculum Graph Poisoning
Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu
-
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification
Haozhen Zhang, Le Yu, Xi Xiao, Qing Li, Francesco Mercaldo, Xiapu Luo, Qixu Liu
-
Unnoticeable Backdoor Attacks on Graph Neural Networks
Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang
-
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding
Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin
-
Event Prediction using Case-Based Reasoning over Knowledge Graphs
Sola Shirai, Debarun Bhattacharjya, Oktie Hassanzadeh
-
Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning
Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang
-
Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph
Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou
-
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning
Xiangrong Zhu, Guangyao Li, Wei Hu
-
Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Manish Singh, Toyotaro Suzumura
-
Knowledge Graph Question Answering with Ambiguous Query
Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong
-
Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment
Qian Li, Shu Guo, Yangyifei Luo, Cheng Ji, Lihong Wang, Jiawei Sheng, Jianxin Li
-
Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs
Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang
-
Unsupervised Entity Alignment for Temporal Knowledge Graphs
Xiaoze Liu, Junyang Wu, Tianyi Li, Lu Chen, Yunjun Gao
-
Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion
Xin Ren, Luyi Bai, Qianwen Xiao, Xiangxi Meng
-
KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion
Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo
-
TRAVERS: A Diversity-Based Dynamic Approach to Iterative Relevance Search over Knowledge Graphs
Ziyang Li, Yu Gu, Yulin Shen, Wei Hu, Gong Cheng
-
Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
Wen Zhang, Yushan Zhu, Mingyang Chen, Yuxia Geng, Yufeng Huang, Yajing Xu, Wenting Song, Huajun Chen
-
TEA: Time-aware Entity Alignment in Knowledge Graphs
Yu Liu, Wen Hua, Kexuan Xin, Saeid Hosseini, Xiaofang Zhou
-
Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models
Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández, Steffen Staab
-
Knowledge Graph Completion with Counterfactual Augmentation
Heng Chang, Jie Cai, Jia Li
-
Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning
Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek F. Abdelzaher
-
Message Function Search for Knowledge Graph Embedding
Shimin Di, Lei Chen
-
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks
Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel B. Work
-
Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space
Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King
-
Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs
Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He
-
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction
Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun
-
Learning to Simulate Crowd Trajectories with Graph Networks
Hongzhi Shi, Quanming Yao, Yong Li
ICDE-2023
-
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Cheng Wu (Tsinghua University); Chaokun Wang (Tsinghua University); Jingcao Xu (Tsinghua University); ZiWei Fang (Tsinghua University); Tiankai Gu (Alibaba Group); Changping Wang (Kuai shou); Yang Song (Kuaishou Inc); Kai Zheng (Kuaishou); Xiaowei Wang (Beijing Kuaishou Technology Co., Ltd.); Guorui Zhou (Kuaishou Inc)*
-
MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning
Shangfei Zheng (Soochow University); Weiqing Wang (Monash University); JIanfeng Qu (Soochow University); Hongzhi Yin (The University of Queensland); Wei Chen (Soochow University); Lei Zhao (Soochow University)*
-
Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction
Zetao Zheng (University of Electronic Science and Technology of China); Jie Shao (University of Electronic Science and Technology of China); Jia Zhu (Zhejiang Normal University); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC))*
-
TDB: Breaking All Hop-Constrained Cycles in Billion-Scale Directed Graphs
You Peng (University of New South Wales); Xuemin Lin (University of New South Wales); Michael R Yu (UNSW); Wenjie Zhang (University of New South Wales); Lu Qin (UTS)*
-
Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Yufeng Zhang (Soochow University); Weiqing Wang (Monash University); Hongzhi Yin (The University of Queensland); Pengpeng Zhao (Soochow University); Wei Chen (Soochow University); Lei Zhao (Soochow University)*
-
When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
Yuchen Fang (Beijing University of Posts and Telecommunications); Yanjun Qin (Beijing University of Posts and Telecommunications); Haiyong Luo (Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences); Fang Zhao (School of Software Engineering, Beijing University of Posts and Telecommunications); Bingbing Xu ( Institute of Computing Technology,University of Chinese Academy of Sciences); Liang Zeng (Tsinghua University); Chenxing Wang (Beijing University of Posts and Telecommunications)*
-
Jointly Attacking Graph Neural Network and its Explanations
“Wenqi FAN (The Hong Kong Polytechnic University); Han Xu (Michigan State University); Wei Jin (Michigan State University); Xiaorui Liu (North Carolina State University); Xianfeng Tang (Amazon); Suhang Wang (Pennsylvania State University); Qing Li (The Hong Kong Polytechnic University); Jiliang Tang (Michigan State University); Jianping Wang (City University of Hong Kong); Charu Aggarwal (IBM)”*
-
Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks
Carl Yang (Emory University); Jiawei Han (UIUC)*
-
CLDG: Contrastive Learning on Dynamic Graphs
Yiming Xu (Xi’an Jiaotong University); Bin Shi (Xi’an jiaotong University); Teng Ma (Xi’an Jiaotong University); Bo Dong (Xi’an Jiaotong University); Haoyi Zhou (Beihang University); Qinghua Zheng (School of Electronic and Information Engineering, Xi’an Jiaotong University)*
-
Relational Message Passing for Fully Inductive Knowledge Graph Completion
Yuxia Geng (Zhejiang University); Jiaoyan Chen (The University of Manchester); Jeff Z. Pan (The University of Edinburgh); Mingyang Chen (Zhejiang University); Song Jiang (Huawei Technologies Co., Ltd); Wen Zhang (Zhejiang University); Huajun Chen (Zhejiang University)*
-
Layer-refined Graph Convolutional Networks for Recommendation
Xin Zhou (Nanyang Technological University); Donghui Lin (Okayama University); Yong Liu (Nanyang Technological University); Chunyan Miao (NTU)*
-
A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation
Huizi Wu (Shanghai University of Finance and Economics); Hui Fang (Shanghai University of Finance and Economics); Zhu Sun (ASTAR); Cong Geng (Shanghai University of Finance and Economics); Xinyu Kong (Ant Group); Yew Soon Ong (Nanyang Technological University, Nanyang View, Singapore)
-
HyGNN: Drug-Drug Interaction Prediction via Hypergraph Neural Network
Khaled Mohammed Saifuddin (Georgia State University); Briana Bumgardner (Rice University); Farhan Tanvir (Oklahoma State University); Esra Akbas (Georgia State University)*
-
Demystifying Bitcoin Address Behavior via Graph Neural Networks
Zhengjie Huang (Zhejiang University); Yunyang Huang (UESTC); Peng Qian (Zhejiang University); Jianhai Chen (Zhejiang University); Qinming He (Zhejiang University)*
-
RETIA: Relation-Entity Twin-Interact Aggregation for Temporal Knowledge Graph Extrapolation
Kangzheng Liu (Huazhong University of Science and Technology); Feng Zhao (Huazhong University of Science and Technology); Guandong Xu (University of Technology Sydney, Australia); Xianzhi Wang (University of Technology Sydney); Hai Jin (Huazhong University of Science and Technology)*
-
Air-Ground Spatial Crowdsourcing with UAV Carriers by Geometric Graph Convolutional Multi-Agent Deep Reinforcement Learning
Yu Wang (Beijing Institute of Technology); Jingfei Wu (Beijing Institute of Technology); Hua Xingyuan (School of Computer Science Beijing Institute of Technology); Chi Harold Liu (Beijing Institute of Technology); Guozheng Li (Beijing Institute of Technology); Jianxin Zhao (Beijing Institute of Technology); Ye Yuan ( Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)*
-
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting
Yusheng Zhao (Peking University); Xiao Luo (UCLA); Wei Ju (Peking University); Chong Chen (Peking University); Xian-Sheng Hua (Terminus Group); Ming Zhang (Peking University)*
-
Disentangled Graph Social Recommendation
Lianghao Xia (University of Hong Kong); Yizhen Shao (South China University of Technology); Chao Huang (University of Hong Kong); Yong Xu (South China University of Technology); Huance Xu (South China University of Technology); Jian Pei (Simon Fraser University)*
-
Fast Unsupervised Graph Embedding via Graph Zoom Learning
Ziyang Liu (Tsinghua University); Chaokun Wang (Tsinghua University); Yunkai Lou (Tsinghua University); Hao Feng (Tsinghua University)*
-
AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network
Guanghui Zhu (Nanjing University); zhu zhennan (Nanjing University); Wenjie Wang (Nanjing University); Zhuoer Xu (Nanjing University); Chunfeng Yuan (Nanjing University); Yihua Huang (Nanjing University)*
-
Multimodal Biological Knowledge Graph Completion via Triple Co-attention Mechanism
Derong Xu (University of Science and Technology of China); jingbo zhou (Baidu Research); Tong Xu (University of Science and Technology of China); yuan xia (baidu); Ji Liu (Baidu Research); Enhong Chen (University of Science and Technology of China); Dejing Dou (Baidu)*
-
SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs
Xiao Qin (AWS AI/ML); Nasrullah Sheikh (IBM); Chuan Lei (Amazon Web Services); Berthold Reinwald (IBM Research-Almaden); Giacomo Domeniconi (U.S. Bank)*
SIGMOD-2023
-
Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation
Yangxin Fan (Case Western Reserve University); Xuanji Yu (Case Western Reserve University); Raymond Wieser (Case Western Reserve University); David Meakin (SunPower Corporation); Avishai Shaton (SolarEdge Technologies); Jean-Nicolas Jaubert (CSI Solar Co.Ltd.); Robert Flottemesch (Brookfield Renewable U.S.); Michael Howell (C2 Energy Capital); Jennifer Braid (Sandia National Labs); Laura Bruckman (Case Western Reserve University); Roger H French (Case Western Reserve University); Yinghui Wu (Case Western Reserve University)*
-
Caerus: A Caching-based Framework for Scalable Temporal Graph Neural Networks
Yiming Li (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology); Mingxuan Yuan (Huawei)*
-
Scalable and Efficient Full-Graph GNN Training for Large Graphs
Xinchen Wan (HKUST); Kaiqiang Xu (HKUST); Xudong Liao (HKUST); Yilun Jin (The Hong Kong University of Science and Technology); Kai Chen (HKUST); Xin Jin (Peking University)
-
EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs
Haoyang Li (The Hong Kong University of Science and Technology); Lei Chen (Hong Kong University of Science and Technology);
-
DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU
Xin Zhang (Hong Kong University of Science and Technology); Yanyan Shen (Shanghai Jiao Tong University); Yingxia Shao (BUPT); Lei Chen (Hong Kong University of Science and Technology)
IJCAI-2022
-
Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network
Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran
-
Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors
Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu
-
Learning Graph-based Residual Aggregation Network for Group Activity Recognition
Wei Li, Tianzhao Yang, Xiao Wu, Zhaoquan Yuan
-
Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting
Yu Tian, Xingliang Huang, Ruigang Niu, Hongfeng Yu, Peijin Wang, Xian Sun
-
Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation
Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen
-
Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies
Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar
-
Hypergraph Structure Learning for Hypergraph Neural Networks
Derun Cai, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, Hongyan Li
-
Entity Alignment with Reliable Path Reasoning and Relation-aware Heterogeneous Graph Transformer
Weishan Cai, Wenjun Ma, Jieyu Zhan, Yuncheng Jiang
-
Can Abnormality be Detected by Graph Neural Networks
Ziwei Chai, Siqi You, Yang Yang, Shiliang Pu, Jiarong Xu, Haoyang Cai, Weihao Jiang
-
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng
-
Filtration-Enhanced Graph Transformation
Zijian Chen, Rong-Hua Li, Hongchao Qin, Huanzhong Duan, Yanxiong Lu, Qiangqiang Dai, Guoren Wang
-
Modeling Precursors for Temporal Knowledge Graph Reasoning via Auto-encoder Structure
Yifu Gao, Linhui Feng, Zhigang Kan, Yi Han, Linbo Qiao, Dongsheng Li
-
Self-supervised Graph Neural Networks for Multi-behavior Recommendation
Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao
-
MERIT: Learning Multi-level Representations on Temporal Graphs
Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen
-
GraphDIVE: Graph Classification by Mixture of Diverse Experts
Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan
-
A Sparse-Motif Ensemble Graph Convolutional Network against Over-smoothing
Xuan Jiang, Zhiyong Yang, Peisong Wen, Li Su, Qingming Huang
-
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan
-
RAW-GNN: RAndom Walk Aggregation based Graph Neural Network
Di Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang
-
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs
Hongwei Jin, Xun Chen
-
TGNN: A Joint Semi-supervised Framework for Graph-level Classification
Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang
-
TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning
Yujia Li, Shiliang Sun, Jing Zhao
-
Raising the Bar in Graph-level Anomaly Detection
Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
-
Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention
Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora D. Salim
-
Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network
Yifei Sun, Haoran Deng, Yang Yang, Chunping Wang, Jiarong Xu, Renhong Huang, Linfeng Cao, Yang Wang, Lei Chen
-
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang
-
Augmenting Knowledge Graphs for Better Link Prediction
Jiang Wang, Filip Ilievski, Pedro A. Szekely, Ke-Thia Yao
-
FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs
Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
-
Ensemble Multi-Relational Graph Neural Networks
Yuling Wang, Hao Xu, Yanhua Yu, Mengdi Zhang, Zhenhao Li, Yuji Yang, Wei Wu
-
Multi-Graph Fusion Networks for Urban Region Embedding
Shangbin Wu, Xu Yan, Xiaoliang Fan, Shirui Pan, Shichao Zhu, Chuanpan Zheng, Ming Cheng, Cheng Wang
-
Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphs
Xiaohan Xu, Peng Zhang, Yongquan He, Chengpeng Chao, Chaoyang Yan
-
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex X. Liu
-
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun
-
GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning
Weiqi Zhang, Chen Zhang, Fugee Tsung
-
Enhancing Sequential Recommendation with Graph Contrastive Learning
Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao
-
Table2Graph: Transforming Tabular Data to Unified Weighted Graph
Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
-
Spiking Graph Convolutional Networks
Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo
-
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks
Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun
-
Proximity Enhanced Graph Neural Networks with Channel Contrast
Wei Zhuo, Guang Tan
-
Personalized Federated Learning With a Graph
Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang
-
Adversarial Explanations for Knowledge Graph Embeddings
Patrick Betz, Christian Meilicke, Heiner Stuckenschmidt
-
Multi-view Unsupervised Graph Representation Learning
Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu
-
Bootstrapping Informative Graph Augmentation via A Meta Learning Approach
Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun, Changwen Zheng
-
Attributed Graph Clustering with Dual Redundancy Reduction
Lei Gong, Sihang Zhou, Wenxuan Tu, Xinwang Liu
-
Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks
Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan
-
Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan
-
On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration
Di Jiang, Yuan Cao, Qiang Yang
-
Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search
Kun Jing, Jungang Xu, Pengfei Li
-
DyGRAIN: An Incremental Learning Framework for Dynamic Graphs
Seoyoon Kim, Seongjun Yun, Jaewoo Kang
-
SGAT: Simplicial Graph Attention Network
See Hian Lee, Feng Ji, Wee Peng Tay
-
Rethinking the Setting of Semi-supervised Learning on Graphs
Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang
-
Deep Graph Matching for Partial Label Learning
Gengyu Lyu, Yanan Wu, Songhe Feng
-
Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering
Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini
-
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation
Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla
-
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla
-
Initializing Then Refining: A Simple Graph Attribute Imputation Network
Wenxuan Tu, Sihang Zhou, Xinwang Liu, Yue Liu, Zhiping Cai, En Zhu, Changwang Zhang, Jieren Cheng
-
EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion
Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan
-
A Simple yet Effective Method for Graph Classification
Junran Wu, Shangzhe Li, Jianhao Li, Yicheng Pan, Ke Xu
-
Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders
Xinxing Wu, Qiang Cheng
-
Information Augmentation for Few-shot Node Classification
Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu
-
Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning
Yalan Ye, Tongjie Pan, Qianhe Meng, Jingjing Li, Li Lu
-
Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport
Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
-
Hierarchical Diffusion Scattering Graph Neural Network
Ke Zhang, Xinyan Pu, Jiaxing Li, Jiasong Wu, Huazhong Shu, Youyong Kong
-
RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning
Yun Zhu, Jianhao Guo, Fei Wu, Siliang Tang
-
Subsequence-based Graph Routing Network for Capturing Multiple Risk Propagation Processes
Rui Cheng, Qing Li
-
Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network
Alex Mathai, Sambaran Bandyopadhyay, Utkarsh Desai, Srikanth Tamilselvam
-
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang
-
FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting
Xuan Rao, Hao Wang, Liang Zhang, Jing Li, Shuo Shang, Peng Han
-
Effective Graph Context Representation for Document-level Machine Translation
Kehai Chen, Muyun Yang, Masao Utiyama, Eiichiro Sumita, Rui Wang, Min Zhang
-
Interactive Information Extraction by Semantic Information Graph
Siqi Fan, Yequan Wang, Jing Li, Zheng Zhang, Shuo Shang, Peng Han
-
Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation
Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li
-
Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning
Bowen Xing, Ivor W. Tsang
-
Contrastive Graph Transformer Network for Personality Detection
Yangfu Zhu, Linmei Hu, Xinkai Ge, Wanrong Peng, Bin Wu
-
Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture
Anoushka Vyas, Sambaran Bandyopadhyay
-
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie
ICML-2022
-
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters
Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
-
Convergence of Invariant Graph Networks
Chen Cai, Yusu Wang
-
Structure-Aware Transformer for Graph Representation Learning
Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt
-
Faster Fundamental Graph Algorithms via Learned Predictions
Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang
-
Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection
Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou
-
Optimization-Induced Graph Implicit Nonlinear Diffusion
Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
-
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers
Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten
-
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen
-
SE(3) Equivariant Graph Neural Networks with Complete Local Frames
Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu
-
pathGCN: Learning General Graph Spatial Operators from Paths
Moshe Eliasof, Eldad Haber, Eran Treister
-
p-Laplacian Based Graph Neural Networks
Guoji Fu, Peilin Zhao, Yatao Bian
-
On the Equivalence Between Temporal and Static Equivariant Graph Representations
Jianfei Gao, Bruno Ribeiro
-
Large-Scale Graph Neural Architecture Search
Chaoyu Guan, Xin Wang, Hong Chen, Ziwei Zhang, Wenwu Zhu
-
Understanding and Improving Knowledge Graph Embedding for Entity Alignment
Lingbing Guo, Qiang Zhang, Zequn Sun, Mingyang Chen, Wei Hu, Huajun Chen
-
G-Mixup: Graph Data Augmentation for Graph Classification
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu
-
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks
Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu
-
Going Deeper into Permutation-Sensitive Graph Neural Networks
Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He
-
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
David Ireland, Giovanni Montana
-
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Jaehyeong Jo, Seul Lee, Sung Ju Hwang
-
Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning
Hidetaka Kamigaito, Katsuhiko Hayashi
-
Simultaneous Graph Signal Clustering and Graph Learning
Abdullah Karaaslanli, Selin Aviyente
-
DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting
Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, Pyang Li
-
G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters
Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin
-
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
-
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning
Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua
-
HousE: Knowledge Graph Embedding with Householder Parameterization
Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
-
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
-
Boosting Graph Structure Learning with Dummy Nodes
Xin Liu, Jiayang Cheng, Yangqiu Song, Xin Jiang
-
Local Augmentation for Graph Neural Networks
Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu
-
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer
-
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism
Siqi Miao, Mia Liu, Pan Li
-
SpeqNets: Sparsity-aware permutation-equivariant graph networks
Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh
-
A Theoretical Comparison of Graph Neural Network Extensions
Pál András Papp, Roger Wattenhofer
-
Nonlinear Feature Diffusion on Hypergraphs
Konstantin Prokopchik, Austin R. Benson, Francesco Tudisco
-
Graph Neural Architecture Search Under Distribution Shifts
Yijian Qin, Xin Wang, Ziwei Zhang, Pengtao Xie, Wenwu Zhu
-
Graph-Coupled Oscillator Networks
T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein
-
Rethinking Graph Neural Networks for Anomaly Detection
Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li
-
Cross-Space Active Learning on Graph Convolutional Networks
Yufei Tao, Hao Wu, Shiyuan Deng
-
What Dense Graph Do You Need for Self-Attention
Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou, Xuanjing Huang, Xipeng Qiu
-
How Powerful are Spectral Graph Neural Networks
Xiyuan Wang, Muhan Zhang
-
Structural Entropy Guided Graph Hierarchical Pooling
Junran Wu, Xueyuan Chen, Ke Xu, Shangzhe Li
-
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning
Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li
-
Self-Supervised Representation Learning via Latent Graph Prediction
Yaochen Xie, Zhao Xu, Shuiwang Ji
-
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
-
Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning
Ling Yang, Shenda Hong
-
A New Perspective on the Effects of Spectrum in Graph Neural Networks
Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, Baocai Yin
-
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks
Zhaoning Yu, Hongyang Gao
-
GraphFM: Improving Large-Scale GNN Training via Feature Momentum
Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
-
Deep and Flexible Graph Neural Architecture Search
Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, Bin Cui
-
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning
Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui
-
Learning to Solve PDE-constrained Inverse Problems with Graph Networks
Qingqing Zhao, David B. Lindell, Gordon Wetzstein
-
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang
KDD-2022
-
Motif Prediction with Graph Neural Networks
Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler
-
Efficient Join Order Selection Learning with Graph-based Representation
Jin Chen, Guanyu Ye, Yan Zhao, Shuncheng Liu, Liwei Deng, Xu Chen, Rui Zhou, Kai Zheng
-
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation
Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King
-
On Structural Explanation of Bias in Graph Neural Networks
Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li
-
FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks
Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang
-
Meta-Learned Metrics over Multi-Evolution Temporal Graphs
Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He
-
Subset Node Anomaly Tracking over Large Dynamic Graphs
Xingzhi Guo, Baojian Zhou, Steven Skiena
-
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong
-
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation
Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
-
GraphMAE: Self-Supervised Masked Graph Autoencoders
Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang
-
Global Self-Attention as a Replacement for Graph Convolution
Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
-
Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs
Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou Sun
-
Detecting Cash-out Users via Dense Subgraphs
Yingsheng Ji, Zheng Zhang, Xinlei Tang, Jiachen Shen, Xi Zhang, Guangwen Yang
-
A Spectral Representation of Networks: The Path of Subgraphs
Shengmin Jin, Hao Tian, Jiayu Li, Reza Zafarani
-
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
-
Condensing Graphs via One-Step Gradient Matching
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin
-
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Jian Kang, Qinghai Zhou, Hanghang Tong
-
CoRGi: Content-Rich Graph Neural Networks with Attention
Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis
-
FlowGEN: A Generative Model for Flow Graphs
Furkan Kocayusufoglu, Arlei Silva, Ambuj K. Singh
-
Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation
Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan
-
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction
Han Li, Dan Zhao, Jianyang Zeng
-
Domain Adaptation in Physical Systems via Graph Kernel
Haoran Li, Hanghang Tong, Yang Weng
-
Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning
Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou
-
Graph Structural Attack by Perturbing Spectral Distance
Lu Lin, Ethan Blaser, Hongning Wang
-
Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems
Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao
-
User-Event Graph Embedding Learning for Context-Aware Recommendation
Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming
-
Graph-in-Graph Network for Automatic Gene Ontology Description Generation
Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang
-
Joint Knowledge Graph Completion and Question Answering
Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong
-
RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams
Qu Liu, Tingjian Ge
-
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries
Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang
-
UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs
Yang Liu, Xiang Ao, Fuli Feng, Qing He
-
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang
-
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer
Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang
-
Learning Causal Effects on Hypergraphs
Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan
-
Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration
Yifan Qi, Weiguo Zheng, Liang Hong, Lei Zou
-
Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning
Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang
-
Graph-Flashback Network for Next Location Recommendation
Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han
-
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
-
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu
-
GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks
Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li
-
Learning on Graphs with Out-of-Distribution Nodes
Yu Song, Donglin Wang
-
Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification
Zixing Song, Yifei Zhang, Irwin King
-
Causal Attention for Interpretable and Generalizable Graph Classification
Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua
-
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks
Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang
-
Streaming Graph Neural Networks with Generative Replay
Junshan Wang, Wenhao Zhu, Guojie Song, Liang Wang
-
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage
Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr
-
Graph Neural Networks with Node-wise Architecture
Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding
-
Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction
Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang
-
Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation
Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, Zibin Zheng
-
Self-Supervised Hypergraph Transformer for Recommender Systems
Lianghao Xia, Chao Huang, Chuxu Zhang
-
Ultrahyperbolic Knowledge Graph Embeddings
Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab
-
Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach
Ge Yan, Yehui Tang, Junchi Yan
-
Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation
Chen-Hsu Yang, Chih-Ya Shen
-
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li
-
TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation
Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi
-
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting
Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong
-
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, U Kang
-
ROLAND: Graph Learning Framework for Dynamic Graphs
Jiaxuan You, Tianyu Du, Jure Leskovec
-
Multiplex Heterogeneous Graph Convolutional Network
Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong
-
Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification
Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai
-
Variational Graph Author Topic Modeling
Delvin Ce Zhang, Hady Wirawan Lauw
-
Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer
Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang
-
Model Degradation Hinders Deep Graph Neural Networks
Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui
-
Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks
Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang
-
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King
-
Instant Graph Neural Networks for Dynamic Graphs
Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang
-
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications
Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra
-
Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding
Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu
-
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks
Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng
-
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning
Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang
-
Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks
Shengyu Chen, Jacob A. Zwart, Xiaowei Jia
-
AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks
Tianyi Chen, Charalampos E. Tsourakakis
-
Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning
Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong
-
Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning
Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong
-
Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series
Siho Han, Simon S. Woo
-
ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps
Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng
-
Graph Neural Network Training and Data Tiering
Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu
-
GraphWorld: Fake Graphs Bring Real Insights for GNNs
John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi
-
Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads
Bochen Pang, Chaozhuo Li, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang
-
Friend Recommendations with Self-Rescaling Graph Neural Networks
Xiran Song, Jianxun Lian, Hong Huang, Mingqi Wu, Hai Jin, Xing Xie
-
A Graph Learning Based Framework for Billion-Scale Offline User Identification
Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou
-
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou
-
Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks
Zhiyuan Wang, Fan Zhou, Wenxuan Zeng, Goce Trajcevski, Chunjing Xiao, Yong Wang, Kai Chen
-
Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction
Haomin Wen, Youfang Lin, Xiaowei Mao, Fan Wu, Yiji Zhao, Haochen Wang, Jianbin Zheng, Lixia Wu, Haoyuan Hu, Huaiyu Wan
-
Graph Neural Networks for Multimodal Single-Cell Data Integration
Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang
-
Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator
Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec
-
Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph
Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang
-
Graph Attention Multi-Layer Perceptron
Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui
-
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs
Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis
-
Dynamic Graph Segmentation for Deep Graph Neural Networks
Johan Kok Zhi Kang, Suwei Yang, Suriya Venkatesan, Sien Yi Tan, Feng Cheng, Bingsheng He
-
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks
Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao
SIGIR-2022
-
Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu
-
Hypergraph Contrastive Collaborative Filtering
Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang
-
Graph Trend Filtering Networks for Recommendation
Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
-
Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering
Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao
-
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer
Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao
-
DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph
Wenwen Gong, Xuyun Zhang, Yifei Chen, Qiang He, Amin Beheshti, Xiaolong Xu, Chao Yan, Lianyong Qi
-
Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing
Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu
-
Few-shot Node Classification on Attributed Networks with Graph Meta-learning
Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan
-
Personalized Fashion Compatibility Modeling via Metapath-guided Heterogeneous Graph Learning
Weili Guan, Fangkai Jiao, Xuemeng Song, Haokun Wen, Chung-Hsing Yeh, Xiaojun Chang
-
KETCH: Knowledge Graph Enhanced Thread Recommendation in Healthcare Forums
Limeng Cui, Dongwon Lee
-
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations
Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras
-
Co-clustering Interactions via Attentive Hypergraph Neural Network
Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang
-
Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction
Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang, Tianzhe Zhao
-
Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
Xiang Chen, Ningyu Zhang, Lei Li, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen
-
Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective
Ying Zhou, Xuanang Chen, Ben He, Zheng Ye, Le Sun
-
Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding
Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen
-
Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning
Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan, Lingling Zhang
-
Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation
Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan
-
Learning Graph-based Disentangled Representations for Next POI Recommendation
Zhaobo Wang, Yanmin Zhu, Haobing Liu, Chunyang Wang
-
Less is More: Reweighting Important Spectral Graph Features for Recommendation
Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine
-
A Review-aware Graph Contrastive Learning Framework for Recommendation
Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li
-
Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation
Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, Quoc Viet Hung Nguyen
-
Knowledge Graph Contrastive Learning for Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li
-
Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification
Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen
-
An Attribute-Driven Mirror Graph Network for Session-based Recommendation
Siqi Lai, Erli Meng, Fan Zhang, Chenliang Li, Bin Wang, Aixin Sun
-
AutoGSR: Neural Architecture Search for Graph-based Session Recommendation
Jingfan Chen, Guanghui Zhu, Haojun Hou, Chunfeng Yuan, Yihua Huang
-
Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders
Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher
-
Multi-modal Graph Contrastive Learning for Micro-video Recommendation
Zixuan Yi, Xi Wang, Iadh Ounis, Craig MacDonald
-
Adversarial Graph Perturbations for Recommendations at Scale
Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang
-
Graph Capsule Network with a Dual Adaptive Mechanism
Xiangping Zheng, Xun Liang, Bo Wu, Yuhui Guo, Xuan Zhang
-
Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation
Yinfeng Li, Chen Gao, Hengliang Luo, Depeng Jin, Yong Li
-
Distilling Knowledge on Text Graph for Social Media Attribute Inference
Quan Li, Xiaoting Li, Lingwei Chen, Dinghao Wu
-
DH-HGCN: Dual Homogeneity Hypergraph Convolutional Network for Multiple Social Recommendations
Jiadi Han, Qian Tao, Yufei Tang, Yuhan Xia
-
GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment
Junseok Lee, Yunhak Oh, Yeonjun In, Namkyeong Lee, Dongmin Hyun, Chanyoung Park
-
GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection
Xu Chen, Qiu Qiu, Changshan Li, Kunqing Xie
-
DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction
Yifan Wang, Yifang Qin, Fang Sun, Bo Zhang, Xuyang Hou, Ke Hu, Jia Cheng, Jun Lei, Ming Zhang
-
An MLP-based Algorithm for Efficient Contrastive Graph Recommendations
Siwei Liu, Iadh Ounis, Craig Macdonald
-
Assessing Scientific Research Papers with Knowledge Graphs
Kexuan Sun, Zhiqiang Qiu, Abel Salinas, Yuzhong Huang, Dong-Ho Lee, Daniel Benjamin, Fred Morstatter, Xiang Ren, Kristina Lerman, Jay Pujara
-
MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization
Qianren Mao, Hongdong Zhu, Junnan Liu, Cheng Ji, Hao Peng, Jianxin Li, Lihong Wang, Zheng Wang
-
LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design
Haoxin Liu
-
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi
NeurIPS-2022
-
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang
-
Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs.
Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka
-
Vision GNN: An Image is Worth Graph of Nodes.
Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu
-
Does GNN Pretraining Help Molecular Representation?
Ruoxi Sun, Hanjun Dai, Adams Wei Yu
-
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.
Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel
-
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein
-
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.
Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro
-
MGNNI: Multiscale Graph Neural Networks with Implicit Layers.
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao
-
NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis.
Jun Zeng, Mingyang Kou, Hailong Yao
-
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding.
Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao
-
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
-
A Practical, Progressively-Expressive GNN.
Lingxiao Zhao, Neil Shah, Leman Akoglu
-
PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.
Yasmin Salehi, Dennis Giannacopoulos
-
NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search.
Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu
-
Decoupled Self-supervised Learning for Graphs.
Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
-
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs.
Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji
-
Revisiting Heterophily For Graph Neural Networks.
Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup
-
Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats.
Hongwei Jin, Zishun Yu, Xinhua Zhang
-
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.
Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang
-
GOOD: A Graph Out-of-Distribution Benchmark.
Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji
-
Not too little, not too much: a theoretical analysis of graph (over)smoothing.
Nicolas Keriven
-
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks.
Ching-Yao Chuang, Stefanie Jegelka
-
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum.
Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei
-
S3GC: Scalable Self-Supervised Graph Clustering.
Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain
-
Pseudo-Riemannian Graph Convolutional Networks.
Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab
-
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.
Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N. M. Anoop Krishnan, Sayan Ranu
-
Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy.
Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen
-
Redundancy-Free Message Passing for Graph Neural Networks.
Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li
-
Association Graph Learning for Multi-Task Classification with Category Shifts.
Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring
-
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.
Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei
-
How Powerful are K-hop Message Passing Graph Neural Networks.
Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang
-
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs.
Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok
-
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture.
Libin Zhu, Chaoyue Liu, Misha Belkin
-
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking.
Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
-
Geodesic Graph Neural Network for Efficient Graph Representation Learning.
Lecheng Kong, Yixin Chen, Muhan Zhang
-
High-Order Pooling for Graph Neural Networks with Tensor Decomposition.
Chenqing Hua, Guillaume Rabusseau, Jian Tang
-
Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.
Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu
-
GraphQNTK: Quantum Neural Tangent Kernel for Graph Data.
Yehui Tang, Junchi Yan
-
On the Robustness of Graph Neural Diffusion to Topology Perturbations.
Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay
-
Few-shot Relational Reasoning via Connection Subgraph Pretraining.
Qian Huang, Hongyu Ren, Jure Leskovec
-
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited.
Mingguo He, Zhewei Wei, Ji-Rong Wen
-
Evaluating Graph Generative Models with Contrastively Learned Features.
Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland
-
An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries.
Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M. Anderson, Henry van den Bedem
-
Are Defenses for Graph Neural Networks Robust?
Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski
-
Equivariant Graph Hierarchy-Based Neural Networks.
Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong
-
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination.
Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu
-
Template based Graph Neural Network with Optimal Transport Distances.
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
-
Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.
Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li
-
Learning Invariant Graph Representations for Out-of-Distribution Generalization.
Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu
-
Task-Agnostic Graph Explanations.
Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji
-
A Variational Edge Partition Model for Supervised Graph Representation Learning.
Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
-
CGLB: Benchmark Tasks for Continual Graph Learning.
Xikun Zhang, Dongjin Song, Dacheng Tao
-
What Makes Graph Neural Networks Miscalibrated?
Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers
-
Analyzing Data-Centric Properties for Graph Contrastive Learning.
Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
-
Learning Bipartite Graphs: Heavy Tails and Multiple Components.
José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar
-
Graph Self-supervised Learning with Accurate Discrepancy Learning.
Dongki Kim, Jinheon Baek, Sung Ju Hwang
-
Recipe for a General, Powerful, Scalable Graph Transformer.
Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
-
Pure Transformers are Powerful Graph Learners.
Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
-
Periodic Graph Transformers for Crystal Material Property Prediction.
Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji
-
Co-Modality Graph Contrastive Learning for Imbalanced Node Classification.
Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang
-
Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning.
Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison
-
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs.
Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek F. Abdelzaher
-
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering.
Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang
-
Neural Topological Ordering for Computation Graphs.
Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi
-
Graph Learning Assisted Multi-Objective Integer Programming.
Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin
-
Exact Shape Correspondence via 2D graph convolution.
Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng
-
SHINE: SubHypergraph Inductive Neural nEtwork.
Yuan Luo
-
Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks.
Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen
-
Graph Neural Networks with Adaptive Readouts.
David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò
-
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games.
Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun
-
Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs.
Ming Jin, Yuan-Fang Li, Shirui Pan
-
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.
Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro
-
Versatile Multi-stage Graph Neural Network for Circuit Representation.
Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao
-
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation.
Chunyu Wei, Jian Liang, Di Liu, Fei Wang
-
Graph Neural Networks are Dynamic Programmers.
Andrew Joseph Dudzik, Petar Velickovic
-
Ordered Subgraph Aggregation Networks.
Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris
-
Hierarchical Graph Transformer with Adaptive Node Sampling.
Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee
-
MGNNI: Multiscale Graph Neural Networks with Implicit Layers.
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao
-
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.
Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
-
Long Range Graph Benchmark.
Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
-
GREED: A Neural Framework for Learning Graph Distance Functions.
Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan T. Chakaravarthy, Yogish Sabharwal, Sayan Ranu
-
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank.
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong
-
DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection.
Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis
-
Contrastive Language-Image Pre-Training with Knowledge Graphs.
Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang
-
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions.
Masanobu Horie, Naoto Mitsume
-
Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection.
Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal
-
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure.
Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang
-
Non-Linear Coordination Graphs.
Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang
-
CLEAR: Generative Counterfactual Explanations on Graphs.
Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
-
Learning Physical Dynamics with Subequivariant Graph Neural Networks.
Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan
-
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu
-
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.
Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell
-
Simplified Graph Convolution with Heterophily.
Sudhanshu Chanpuriya, Cameron Musco
-
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks.
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
-
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks.
Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi
-
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification.
Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan
-
Parameter-free Dynamic Graph Embedding for Link Prediction.
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu
-
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.
Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li
-
Label-invariant Augmentation for Semi-Supervised Graph Classification.
Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu
-
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks.
Chenxiao Yang, Qitian Wu, Junchi Yan
-
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network.
Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan
-
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs.
Zenan Li, Qitian Wu, Fan Nie, Junchi Yan
-
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders.
Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li
-
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
-
Symmetry-induced Disentanglement on Graphs.
Giangiacomo Mercatali, André Freitas, Vikas Garg
-
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks.
Davide Buffelli, Pietro Lió, Fabio Vandin
-
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.
Abdel Ghani Labassi, Didier Chételat, Andrea Lodi
-
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations.
Ivan Marisca, Andrea Cini, Cesare Alippi
-
Robust Graph Structure Learning via Multiple Statistical Tests.
Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
-
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks.
Indradyumna Roy, Soumen Chakrabarti, Abir De
-
Provably expressive temporal graph networks.
Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
-
Uncovering the Structural Fairness in Graph Contrastive Learning.
Ruijia Wang, Xiao Wang, Chuan Shi, Le Song
-
On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs.
Arjun Subramonian, Kai-Wei Chang, Yizhou Sun
-
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.
Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann
-
Neural Approximation of Graph Topological Features.
Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen
-
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective.
Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
-
Graph Neural Network Bandits.
Parnian Kassraie, Andreas Krause, Ilija Bogunovic
-
Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains.
Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia R. Gel, Cuneyt Gurcan Akcora
-
TwiBot-22: Towards Graph-Based Twitter Bot Detection.
Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo
-
Deep Generative Model for Periodic Graphs.
Shiyu Wang, Xiaojie Guo, Liang Zhao
-
PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.
Yasmin Salehi, Dennis Giannacopoulos
-
Deep Bidirectional Language-Knowledge Graph Pretraining.
Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec
-
CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference.
Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen
-
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks
Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf
-
Graph Reordering for Cache-Efficient Near Neighbor Search.
Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
-
Graph Few-shot Learning with Task-specific Structures.
Song Wang, Chen Chen, Jundong Li
-
OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport.
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
AAAI-2022
-
SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds
Qingdong He, Zhengning Wang, Hao Zeng, Yi Zeng, Yijun Liu
-
Graph-Based Point Tracker for 3D Object Tracking in Point Clouds
Minseong Park, Hongje Seong, Wonje Jang, Euntai Kim
-
Learning to Detect 3D Facial Landmarks via Heatmap Regression with Graph Convolutional Network
Yuan Wang, Min Cao, Zhenfeng Fan, Silong Peng
-
Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation
Xixia Xu, Qi Zou, Xue Lin
-
ACGNet: Action Complement Graph Network for Weakly-Supervised Temporal Action Localization
Zichen Yang, Jie Qin, Di Huang
-
Hybrid Graph Neural Networks for Few-Shot Learning
Tianyuan Yu, Sen He, Yi-Zhe Song, Tao Xiang
-
MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-Based Image Captioning
Wenqiao Zhang, Haochen Shi, Jiannan Guo, Shengyu Zhang, Qingpeng Cai, Juncheng Li, Sihui Luo, Yueting Zhuang
-
Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations
Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou
-
Differentially Describing Groups of Graphs
Corinna Coupette, Sebastian Dalleiger, Jilles Vreeken
-
Molecular Contrastive Learning with Chemical Element Knowledge Graph
Yin Fang, Qiang Zhang, Haihong Yang, Xiang Zhuang, Shumin Deng, Wen Zhang, Ming Qin, Zhuo Chen, Xiaohui Fan, Huajun Chen
-
Heterogeneity-Aware Twitter Bot Detection with Relational Graph Transformers
Shangbin Feng, Zhaoxuan Tan, Rui Li, Minnan Luo
-
Orthogonal Graph Neural Networks
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang
-
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks
Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang
-
Block Modeling-Guided Graph Convolutional Neural Networks
Dongxiao He, Chundong Liang, Huixin Liu, Mingxiang Wen, Pengfei Jiao, Zhiyong Feng
-
From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs
Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng
-
TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs
Yushan Liu, Yunpu Ma, Marcel Hildebrandt, Mitchell Joblin, Volker Tresp
-
A Self-Supervised Mixed-Curvature Graph Neural Network
Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu
-
Graph Structure Learning with Variational Information Bottleneck
Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu
-
Exploring Relational Semantics for Inductive Knowledge Graph Completion
Changjian Wang, Xiaofei Zhou, Shirui Pan, Linhua Dong, Zeliang Song, Ying Sha
-
HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting
Chenyu Wang, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, Cyrus Shahabi
-
Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily
Tao Wang, Di Jin, Rui Wang, Dongxiao He, Yuxiao Huang
-
CoCoS: Enhancing Semi-supervised Learning on Graphs with Unlabeled Data via Contrastive Context Sharing
Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau
-
Unsupervised Adversarially Robust Representation Learning on Graphs
Jiarong Xu, Yang Yang, Junru Chen, Xin Jiang, Chunping Wang, Jiangang Lu, Yizhou Sun
-
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs
Jiarong Xu, Yizhou Sun, Xin Jiang, Yanhao Wang, Chunping Wang, Jiangang Lu, Yang Yang
-
Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing
Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo, Xiaochun Cao
-
Multi-Scale Distillation from Multiple Graph Neural Networks
Chunhai Zhang, Jie Liu, Kai Dang, Wenzheng Zhang
-
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks
Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou
-
Multi-View Intent Disentangle Graph Networks for Bundle Recommendation
Sen Zhao, Wei Wei, Ding Zou, Xianling Mao
-
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-Supervision
Jun Zhuang, Mohammad Al Hasan
-
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
Shuangli Li, Jingbo Zhou, Tong Xu, Dejing Dou, Hui Xiong
-
Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs
Chang Lu, Tian Han, Yue Ning
-
DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social Media
Mengzhu Sun, Xi Zhang, Jiaqi Zheng, Guixiang Ma
-
RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning
Hansheng Xue, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, Yu Lin
-
ZINB-Based Graph Embedding Autoencoder for Single-Cell RNA-Seq Interpretations
Zhuohan Yu, Yifu Lu, Yunhe Wang, Fan Tang, Ka-Chun Wong, Xiangtao Li
-
Hierarchical Multi-Supervision Multi-Interaction Graph Attention Network for Multi-Camera Pedestrian Trajectory Prediction
Guoliang Zhao, Yuxun Zhou, Zhanbo Xu, Yadong Zhou, Jiang Wu
-
ER: Equivariance Regularizer for Knowledge Graph Completion
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Qingming Huang
-
Geometry Interaction Knowledge Graph Embeddings
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
-
Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network
Guanzheng Chen, Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, Shangsong Liang
-
How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View
Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li
-
Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long, Yutong Xie, Xianyu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu
-
TempoQR: Temporal Question Reasoning over Knowledge Graphs
Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip R. Howard, Tetiana Grinberg, Nagib Hakim, George Karypis
-
Learning to Walk with Dual Agents for Knowledge Graph Reasoning
Denghui Zhang, Zixuan Yuan, Hao Liu, Xiaodong Lin, Hui Xiong
-
Beyond GNNs: An Efficient Architecture for Graph Problems
Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
-
Graph Neural Controlled Differential Equations for Traffic Forecasting
Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park
-
Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning
Thilini Cooray, Ngai-Man Cheung
-
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning
Kaize Ding, Jianling Wang, James Caverlee, Huan Liu
-
Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao
-
Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples
Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu
-
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels
Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas
-
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks
Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng
-
TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs
Shubham Gupta, Sahil Manchanda, Srikanta Bedathur, Sayan Ranu
-
Cross-Domain Few-Shot Graph Classification
Kaveh Hassani
-
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data
Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
-
Fast Graph Neural Tangent Kernel via Kronecker Sketching
Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo
-
Adaptive Kernel Graph Neural Network
Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao
-
Directed Graph Auto-Encoders
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe
-
Augmentation-Free Self-Supervised Learning on Graphs
Namkyeong Lee, Junseok Lee, Chanyoung Park
-
Robust Graph-Based Multi-View Clustering
Weixuan Liang, Xinwang Liu, Sihang Zhou, Jiyuan Liu, Siwei Wang, En Zhu
-
On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations
Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin
-
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching
Xin Liu, Yangqiu Song
-
Deep Graph Clustering via Dual Correlation Reduction
Yue Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu, Linxuan Song, Xihong Yang, En Zhu
-
fGOT: Graph Distances Based on Filters and Optimal Transport
Hermina Petric Maretic, Mireille El Gheche, Giovanni Chierchia, Pascal Frossard
-
Temporal Knowledge Graph Completion Using Box Embeddings
Johannes Messner, Ralph Abboud, Ismail Ilkan Ceylan
-
Simple Unsupervised Graph Representation Learning
Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu
-
Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks
Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates
-
Deformable Graph Convolutional Networks
Jinyoung Park, Sungdong Yoo, Jihwan Park, Hyunwoo J. Kim
-
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation
Joonhyung Park, Hajin Shim, Eunho Yang
-
Interpretable Neural Subgraph Matching for Graph Retrieval
Indradyumna Roy, Venkata Sai Baba Reddy Velugoti, Soumen Chakrabarti, Abir De
-
Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel
Shota Saito
-
VACA: Designing Variational Graph Autoencoders for Causal Queries
Pablo Sánchez-Martín, Miriam Rateike, Isabel Valera
-
Graph Filtration Kernels
Till Hendrik Schulz, Pascal Welke, Stefan Wrobel
-
EqGNN: Equalized Node Opportunity in Graphs
Uriel Singer, Kira Radinsky
-
Graph Pointer Neural Networks
Tianmeng Yang, Yujing Wang, Zhihan Yue, Yaming Yang, Yunhai Tong, Jing Bai
-
AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators
Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang
-
Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin
-
SAIL: Self-Augmented Graph Contrastive Learning
Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang
-
Low-Pass Graph Convolutional Network for Recommendation
Wenhui Yu, Zixin Zhang, Zheng Qin
-
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning
Yuheng Zhang, Hanghang Tong, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying
-
ProtGNN: Towards Self-Explaining Graph Neural Networks
Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee
-
Structural Landmarking and Interaction Modelling: A "SLIM" Network for Graph Classification
Yaokang Zhu, Kai Zhang, Jun Wang, Haibin Ling, Jie Zhang, Hongyuan Zha
-
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs
Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen
-
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability Using Tree Search and Graph Neural Networks
Kevin Osanlou, Jeremy Frank, Andrei Bursuc, Tristan Cazenave, Eric Jacopin, Christophe Guettier, J. Benton
-
Qubit Routing Using Graph Neural Network Aided Monte Carlo Tree Search
Animesh Sinha, Utkarsh Azad, Harjinder Singh
-
Enhanced Story Comprehension for Large Language Models through Dynamic Document-Based Knowledge Graphs
Berkeley R. Andrus, Yeganeh Nasiri, Shilong Cui, Benjamin Cullen, Nancy Fulda
-
ISEEQ: Information Seeking Question Generation Using Dynamic Meta-Information Retrieval and Knowledge Graphs
Manas Gaur, Kalpa Gunaratna, Vijay Srinivasan, Hongxia Jin
-
Dynamic Key-Value Memory Enhanced Multi-Step Graph Reasoning for Knowledge-Based Visual Question Answering
Mingxiao Li, Marie-Francine Moens
-
LeSICiN: A Heterogeneous Graph-Based Approach for Automatic Legal Statute Identification from Indian Legal Documents
Shounak Paul, Pawan Goyal, Saptarshi Ghosh
-
Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim
-
Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization
Zixing Song, Irwin King
-
DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation
Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, Sheng Wang
-
GraphMemDialog: Optimizing End-to-End Task-Oriented Dialog Systems Using Graph Memory Networks
Jie Wu, Ian G. Harris, Hongzhi Zhao
-
A Graph Convolutional Network with Adaptive Graph Generation and Channel Selection for Event Detection
Zhipeng Xie, Yumin Tu
-
JAKET: Joint Pre-training of Knowledge Graph and Language Understanding
Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng
-
CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting
Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe
-
Accelerating COVID-19 Research with Graph Mining and Transformer-Based Learning
Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael Shtutman, Ilya Safro
ICLR-2022
-
A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?".
Asiri Wijesinghe, Qing Wang
-
Data-Efficient Graph Grammar Learning for Molecular Generation.
Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
-
Expressiveness and Approximation Properties of Graph Neural Networks.
Floris Geerts, Juan L. Reutter
-
Understanding over-squashing and bottlenecks on graphs via curvature.
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
-
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
-
DEGREE: Decomposition Based Explanation for Graph Neural Networks.
Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu
-
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations.
Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick
-
On Evaluation Metrics for Graph Generative Models.
Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor
-
Graph Condensation for Graph Neural Networks.
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
-
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness.
Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
-
Triangle and Four Cycle Counting with Predictions in Graph Streams.
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
-
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs.
Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton
-
Graphon based Clustering and Testing of Networks: Algorithms and Theory.
Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
-
How Attentive are Graph Attention Networks?
Shaked Brody, Uri Alon, Eran Yahav
-
Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation.
Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
-
Large-Scale Representation Learning on Graphs via Bootstrapping.
Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko
-
Top-N: Equivariant Set and Graph Generation without Exchangeability.
Clément Vignac, Pascal Frossard
-
PF-GNN: Differentiable particle filtering based approximation of universal graph representations.
Mohammed Haroon Dupty, Yanfei Dong, Wee Sun Lee
-
Equivariant Graph Mechanics Networks with Constraints.
Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang
-
Convergent Graph Solvers.
Junyoung Park, Jinhyun Choo, Jinkyoo Park
-
GLASS: GNN with Labeling Tricks for Subgraph Representation Learning.
Xiyuan Wang, Muhan Zhang
-
Space-Time Graph Neural Networks.
Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro
-
End-to-End Learning of Probabilistic Hierarchies on Graphs.
Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann
-
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification.
Joonhyung Park, Jaeyun Song, Eunho Yang
-
Why Propagate Alone? Parallel Use of Labels and Features on Graphs.
Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
-
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.
Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
-
Query Embedding on Hyper-Relational Knowledge Graphs.
Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
-
Inductive Relation Prediction Using Analogy Subgraph Embeddings.
Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan
-
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem.
Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok
-
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
-
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis.
Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer
-
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression.
Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu
-
Graph-Relational Domain Adaptation.
Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang
-
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication.
Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin
-
Graph Neural Networks with Learnable Structural and Positional Representations.
Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson
-
Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction.
Mingyue Tang, Pan Li, Carl Yang
-
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective.
Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang
-
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks.
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
-
Neural Methods for Logical Reasoning over Knowledge Graphs.
Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang
-
Graph-Guided Network for Irregularly Sampled Multivariate Time Series.
Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik
-
Explainable GNN-Based Models over Knowledge Graphs.
David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, Boris Motik
-
Pre-training Molecular Graph Representation with 3D Geometry.
Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
-
GRAND++: Graph Neural Diffusion with A Source Term.
Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
-
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs.
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
-
Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms.
Simin Hong, Anthony G. Cohn, David Crossland Hogg
-
Learning Graphon Mean Field Games and Approximate Nash Equilibria.
Kai Cui, Heinz Koeppl
-
Topological Graph Neural Networks.
Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
-
Automated Self-Supervised Learning for Graphs.
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
-
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.
Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic
-
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods.
Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian
-
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery.
Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica Teixeira Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown
-
Spherical Message Passing for 3D Molecular Graphs.
Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji
-
Fairness Guarantees under Demographic Shift.
Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum
-
Learning Guarantees for Graph Convolutional Networks on the Stochastic Block Model.
Wei Lu
-
Graph-based Nearest Neighbor Search in Hyperbolic Spaces.
Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov
-
Discovering Invariant Rationales for Graph Neural Networks.
Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua
-
Do We Need Anisotropic Graph Neural Networks?
Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane
-
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond.
Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
-
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks.
Andrea Cini, Ivan Marisca, Cesare Alippi
-
Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels.
Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui
-
Handling Distribution Shifts on Graphs: An Invariance Perspective.
Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
-
Generalized Demographic Parity for Group Fairness.
Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu
-
Fixed Neural Network Steganography: Train the images, not the network.
Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q. Weinberger
-
A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease.
Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman
-
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph.
Dacheng Yin, Xuanchi Ren, Chong Luo, Yuwang Wang, Zhiwei Xiong, Wenjun Zeng
-
GNN is a Counter? Revisiting GNN for Question Answering.
Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin
-
Neural graphical modelling in continuous-time: consistency guarantees and algorithms.
Alexis Bellot, Kim Branson, Mihaela van der Schaar
-
Learning to Schedule Learning rate with Graph Neural Networks.
Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh
-
GreaseLM: Graph REASoning Enhanced Language Models.
Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec
-
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
-
TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting.
Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia R. Gel
-
GNN-LM: Language Modeling based on Global Contexts via GNN.
Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li
-
Revisiting Over-smoothing in BERT from the Perspective of Graph.
Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok
-
Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series.
Enyan Dai, Jie Chen
-
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design.
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
-
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions.
Nicholas Gao, Stephan Günnemann
-
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions.
Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
-
Context-Aware Sparse Deep Coordination Graphs.
Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang
-
Spanning Tree-based Graph Generation for Molecules.
Sungsoo Ahn, Binghong Chen, Tianzhe Wang, Le Song
-
Equivariant Subgraph Aggregation Networks.
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
WSDM-2022
-
Graph Collaborative Reasoning
Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang
-
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King
-
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
-
Predicting Human Mobility via Graph Convolutional Dual-attentive Networks
Weizhen Dang, Haibo Wang, Shirui Pan, Pei Zhang, Chuan Zhou, Xin Chen, Jilong Wang
-
Efficient Graph Convolution for Joint Node Representation Learning and Clustering
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
-
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
Shen Gao, Yuchi Zhang, Yongliang Wang, Yang Dong, Xiuying Chen, Dongyan Zhao, Rui Yan
-
Multi-Scale Variational Graph AutoEncoder for Link Prediction
Zhihao Guo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang
-
Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction
Jinquan Hang, Zheng Dong, Hongke Zhao, Xin Song, Peng Wang, Hengshu Zhu
-
Triangle Graph Interest Network for Click-through Rate Prediction
Wensen Jiang, Yizhu Jiao, Qingqin Wang, Chuanming Liang, Lijie Guo, Yao Zhang, Zhijun Sun, Yun Xiong, Yangyong Zhu
-
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification
Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang
-
GAGE: Geometry Preserving Attributed Graph Embeddings
Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos
-
Graph Embedding with Hierarchical Attentive Membership
Lu Lin, Ethan Blaser, Hongning Wang
-
Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks
Zihan Liu, Yun Luo, Zelin Zang, Stan Z. Li
-
Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks
Zihan Luo, Jianxun Lian, Hong Huang, Hai Jin, Xing Xie
-
ComGA: Community-Aware Attributed Graph Anomaly Detection
Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, Shan Xue
-
Learning Fair Node Representations with Graph Counterfactual Fairness
Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
-
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation
Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel
-
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation
Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long, Jian Pei
-
EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs
Namyong Park, Fuchen Liu, Purvanshi Mehta, Dana Cristofor, Christos Faloutsos, Yuxiao Dong
-
Attributed Graph Modeling with Vertex Replacement Grammars
Satyaki Sikdar, Neil Shah, Tim Weninger
-
Graph Few-shot Class-incremental Learning
Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
-
Friend Story Ranking with Edge-Contextual Local Graph Convolutions
Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah
-
Scalable Graph Topology Learning via Spectral Densification
Yongyu Wang, Zhiqiang Zhao, Zhuo Feng
-
Profiling the Design Space for Graph Neural Networks based Collaborative Filtering
Zhenyi Wang, Huan Zhao, Chuan Shi
-
Interpretable Relation Learning on Heterogeneous Graphs
Qiang Yang, Qiannan Zhang, Chuxu Zhang, Xiangliang Zhang
-
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
-
Community Trend Prediction on Heterogeneous Graph in E-commerce
Jiahao Yuan, Zhao Li, Pengcheng Zou, Xuan Gao, Jinwei Pan, Wendi Ji, Xiaoling Wang
-
Learning Concept Prerequisite Relations from Educational Data via Multi-Head Attention Variational Graph Auto-Encoders
Juntao Zhang, Nanzhou Lin, Xuelong Zhang, Wei Song, Xiandi Yang, Zhiyong Peng
-
Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network
Kai Zhao, Yukun Zheng, Tao Zhuang, Xiang Li, Xiaoyi Zeng
-
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning
Yushan Zhu, Wen Zhang, Mingyang Chen, Hui Chen, Xu Cheng, Wei Zhang, Huajun Chen
-
A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion
Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao, Weisi Han
WWW-2022
-
Modeling User Behavior with Graph Convolution for Personalized Product Search
Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang
-
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search
Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He
-
Efficient and Effective Similarity Search over Bipartite Graphs
Renchi Yang
-
RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph
Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin, Tarek F. Abdelzaher
-
TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection
Sijia Li, Gaopeng Gou, Chang Liu, Chengshang Hou, Zhenzhen Li, Gang Xiong
-
ALLIE: Active Learning on Large-scale Imbalanced Graphs
Limeng Cui, Xianfeng Tang, Sumeet Katariya, Nikhil Rao, Pallav Agrawal, Karthik Subbian, Dongwon Lee
-
Rethinking Graph Convolutional Networks in Knowledge Graph Completion
Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu
-
Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings
Kai Wang, Yu Liu, Quan Z. Sheng
-
SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs
Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang
-
Knowledge Graph Reasoning with Relational Digraph
Yongqi Zhang, Quanming Yao
-
Path Language Modeling over Knowledge Graphs for Explainable Recommendation
Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang
-
Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data
Jiacheng Huang, Yao Zhao, Wei Hu, Zhen Ning, Qijin Chen, Xiaoxia Qiu, Chengfu Huo, Weijun Ren
-
Can Machine Translation be a Reasonable Alternative for Multilingual Question Answering Systems over Knowledge Graphs
Aleksandr Perevalov, Andreas Both, Dennis Diefenbach, Axel-Cyrille Ngonga Ngomo
-
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning
Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang
-
An Invertible Graph Diffusion Neural Network for Source Localization
Junxiang Wang, Junji Jiang, Liang Zhao
-
SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation
Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li
-
MiDaS: Representative Sampling from Real-world Hypergraphs
Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin
-
CGC: Contrastive Graph Clustering for Community Detection and Tracking
Namyong Park, Ryan A. Rossi, Eunyee Koh, Iftikhar Ahamath Burhanuddin, Sungchul Kim, Fan Du, Nesreen K. Ahmed, Christos Faloutsos
-
Graph Neural Networks Beyond Compromise Between Attribute and Topology
Liang Yang, Wenmiao Zhou, Weihang Peng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao, Dongxiao He
-
Graph Sanitation with Application to Node Classification
Zhe Xu, Boxin Du, Hanghang Tong
-
TREND: TempoRal Event and Node Dynamics for Graph Representation Learning
Zhihao Wen, Yuan Fang
-
Resource-Efficient Training for Large Graph Convolutional Networks with Label-Centric Cumulative Sampling
Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Sanglu Lu
-
Graph Communal Contrastive Learning
Bolian Li, Baoyu Jing, Hanghang Tong
-
Geometric Graph Representation Learning via Maximizing Rate Reduction
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu
-
Dual Space Graph Contrastive Learning
Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu
-
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift
Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou
-
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks
Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li
-
Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily
Xiaojun Ma, Qin Chen, Yuanyi Ren, Guojie Song, Liang Wang
-
Model-Agnostic Augmentation for Accurate Graph Classification
Jaemin Yoo, Sooyeon Shim, U Kang
-
Multimodal Continual Graph Learning with Neural Architecture Search
Jie Cai, Xin Wang, Chaoyu Guan, Yateng Tang, Jin Xu, Bin Zhong, Wenwu Zhu
-
AUC-oriented Graph Neural Network for Fraud Detection
Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He
-
Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation
Sixiao Zhang, Hongxu Chen, Xiangguo Sun, Yicong Li, Guandong Xu
-
Graph-adaptive Rectified Linear Unit for Graph Neural Networks
Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King
-
Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction
Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang
-
Adversarial Graph Contrastive Learning with Information Regularization
Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong
-
Designing the Topology of Graph Neural Networks: A Novel Feature Fusion Perspective
Lanning Wei, Huan Zhao, Zhiqiang He
-
Towards Unsupervised Deep Graph Structure Learning
Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan
-
Polarized Graph Neural Networks
Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang
-
Unbiased Graph Embedding with Biased Graph Observations
Nan Wang, Lu Lin, Jundong Li, Hongning Wang
-
Prohibited Item Detection via Risk Graph Structure Learning
Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du
-
Inflation Improves Graph Neural Networks
Dongxiao He, Rui Guo, Xiaobao Wang, Di Jin, Yuxiao Huang, Wenjun Wang
-
Generating Simple Directed Social Network Graphs for Information Spreading
Christoph Schweimer, Christine Gfrerer, Florian Lugstein, David Pape, Jan A. Velimsky, Robert Elsässer, Bernhard C. Geiger
-
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks
Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun
-
Curvature Graph Generative Adversarial Networks
Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng
-
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices
Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra
-
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily
Lun Du, Xiaozhou Shi, Qiang Fu, Xiaojun Ma, Hengyu Liu, Shi Han, Dongmei Zhang
-
Compact Graph Structure Learning via Mutual Information Compression
Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi
-
ClusterSCL: Cluster-Aware Supervised Contrastive Learning on Graphs
Yanling Wang, Jing Zhang, Haoyang Li, Yuxiao Dong, Hongzhi Yin, Cuiping Li, Hong Chen
-
Graph Neural Network for Higher-Order Dependency Networks
Di Jin, Yingli Gong, Zhiqiang Wang, Zhizhi Yu, Dongxiao He, Yuxiao Huang, Wenjun Wang
-
PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm
Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui
-
Element-guided Temporal Graph Representation Learning for Temporal Sets Prediction
Le Yu, Guanghui Wu, Leilei Sun, Bowen Du, Weifeng Lv
-
Hypercomplex Graph Collaborative Filtering
Anchen Li, Bo Yang, Huan Huo, Farookh Khadeer Hussain
-
Graph Neural Transport Networks with Non-local Attentions for Recommender Systems
Huiyuan Chen, Chin-Chia Michael Yeh, Fei Wang, Hao Yang
-
Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning
Xiting Wang, Kunpeng Liu, Dongjie Wang, Le Wu, Yanjie Fu, Xing Xie
-
GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction
Chunyu Wei, Bing Bai, Kun Bai, Fei Wang
-
Graph-based Extractive Explainer for Recommendations
Peng Wang, Renqin Cai, Hongning Wang
-
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
Zihan Lin, Changxin Tian, Yupeng Hou, Wayne Xin Zhao
-
Evidence-aware Fake News Detection with Graph Neural Networks
Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang
-
Rumor Detection on Social Media with Graph Adversarial Contrastive Learning
Tiening Sun, Zhong Qian, Sujun Dong, Peifeng Li, Qiaoming Zhu
-
VisGNN: Personalized Visualization Recommendationvia Graph Neural Networks
Fayokemi Ojo, Ryan A. Rossi, Jane Hoffswell, Shunan Guo, Fan Du, Sungchul Kim, Chang Xiao, Eunyee Koh
-
Revisiting Graph based Social Recommendation: A Distillation Enhanced Social Graph Network
Ye Tao, Ying Li, Su Zhang, Zhirong Hou, Zhonghai Wu
-
DiriE: Knowledge Graph Embedding with Dirichlet Distribution
Feiyang Wang, Zhongbao Zhang, Li Sun, Junda Ye, Yang Yan
-
STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation
Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, Jie Tang
-
GRAND+: Scalable Graph Random Neural Networks
Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang
-
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network
Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu
-
Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes
Hui Hu, Lu Cheng, Jayden Parker Vap, Mike Borowczak
ICDE-2022
-
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection
Yulin Zhu, Yuni Lai, Kaifa Zhao, Xiapu Luo, Mingquan Yuan, Jian Ren, Kai Zhou
-
Accurate and Scalable Graph Neural Networks for Billion-Scale Graphs
Juxiang Zeng, Pinghui Wang, Lin Lan, Junzhou Zhao, Feiyang Sun, Jing Tao, Junlan Feng, Min Hu, Xiaohong Guan
-
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation
Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King
-
Academic Expert Finding via
$(k, \mathcal{P})$ -Core based Embedding over Heterogeneous GraphsXiaoliang Xu, Jun Liu, Yuxiang Wang, Xiangyu Ke
-
AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020
Jin Xu, Mingjian Chen, Jianqiang Huang, Xingyuan Tang, Ke Hu, Jian Li, Jia Cheng, Jun Lei
-
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
Kyuhan Lee, Jihoon Ko, Kijung Shin
-
$O^{2}$ -SiteRec: Store Site Recommendation under the O2O Model via Multi-graph Attention NetworksHua Yan, Shuai Wang, Yu Yang, Baoshen Guo, Tian He, Desheng Zhang
-
A Data-Driven Spatial-Temporal Graph Neural Network for Docked Bike Prediction
Guanyao Li, Xiaofeng Wang, Gunarto Sindoro Njoo, Shuhan Zhong, S.-H. Gary Chan, Chih-Chieh Hung, Wen-Chih Peng
-
Black-box Adversarial Attack and Defense on Graph Neural Networks
Haoyang Li, Shimin Di, Zijian Li, Lei Chen, Jiannong Cao
-
MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks
Panpan Qi, Dan Li, See-Kiong Ng
-
On Compressing Temporal Graphs
Panagiotis Liakos, Katia Papakonstantinopoulou, Theodore Stefou, Alex Delis
-
Dynamic Hypergraph Convolutional Network
Nan Yin, Fuli Feng, Zhigang Luo, Xiang Zhang, Wenjie Wang, Xiao Luo, Chong Chen, Xian-Sheng Hua
-
PSP: Progressive Space Pruning for Efficient Graph Neural Architecture Search
Guanghui Zhu, Wenjie Wang, Zhuoer Xu, Feng Cheng, Mengchuan Qiu, Chunfeng Yuan, Yihua Huang
-
HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache
Sicong Dong, Xupeng Miao, Pengkai Liu, Xin Wang, Bin Cui, Jianxin Li
-
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction
Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei
-
BA-GNN: On Learning Bias-Aware Graph Neural Network
Zhengyu Chen, Teng Xiao, Kun Kuang
-
VICS-GNN: A Visual Interactive System for Community Search via Graph Neural Network
Jiazun Chen, Jun Gao
-
Tower Bridge Net (TB-Net): Bidirectional Knowledge Graph Aware Embedding Propagation for Explainable Recommender Systems
Shendi Wang, Haoyang Li, Caleb Chen Cao, Xiao-Hui Li, Ng Ngai Fai, Jianxin Liu, Xun Xue, Hu Song, Jinyu Li, Guangye Gu, Lei Chen
-
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce
Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang
SIGMOD-2022
-
Entity Resolution with Hierarchical Graph Attention Networks
Dezhong Yao, Yuhong Gu, Gao Cong, Hai Jin, Xinqiao Lv
-
Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways
Pei-Yu Hou, Daniel Robert Korn, Cleber C. Melo-Filho, David R. Wright, Alexander Tropsha, Rada Chirkova
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Explaining Link Prediction Systems based on Knowledge Graph Embeddings
Andrea Rossi, Donatella Firmani, Paolo Merialdo, Tommaso Teofili