| DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption |
Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo |
here |
| Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks |
Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo |
here |
| PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation |
Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, Wentao Liu |
here |
| Graphpulse: Topological representations for temporal graph property prediction |
Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Akcora |
here |
| GnnX-Bench: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking |
Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj K Singh, Sourav Medya, Sayan Ranu |
here |
| GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs |
Pengcheng Jiang, Cao Xiao, Adam Cross, Jimeng Sun |
here |
| Improving Generalization in Equivariant Graph Neural Networks with Physical Inductive Biases |
Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong |
here |
| BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs |
Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, RISHITA ANUBHAI |
here |
| Scalable and Effective Implicit Graph Neural Networks on Large Graphs |
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao |
here |
| A Differentially Private Clustering Algorithm for Well-Clustered Graphs |
Weiqiang He, Hendrik Fichtenberger, Pan Peng |
here |
| Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs |
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura |
here |
| Contrastive Learning is Spectral Clustering on Similarity Graph |
Yifan Zhang, Zhiquan Tan, Jingqin Yang, Yang Yuan |
here |
| Talk like a Graph: Encoding Graphs for Large Language Models |
Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi |
here |
| Uncertainty-aware Graph-based Hyperspectral Image Classification |
Linlin Yu, Yifei Lou, Feng Chen |
here |
| Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks |
Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z Li |
here |
| On the Stability of Expressive Positional Encodings for Graph Neural Networks |
Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li |
here |
|
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning |
Adyasha Maharana, Prateek Yadav, Mohit Bansal |
here |
| NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks |
Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth McMillan, Risto Miikkulainen |
here |
| Neural Common Neighbor with Completion for Link Prediction |
Xiyuan Wang, Haotong Yang, Muhan Zhang |
here |
| From Graphs to Hypergraphs: Hypergraph Projection and its Remediation |
Yanbang Wang, Jon Kleinberg |
here |
| Counting Graph Substructures with Graph Neural Networks |
Charilaos Kanatsoulis, Alejandro Ribeiro |
here |
| Adversarial Attacks on Fairness of Graph Neural Networks |
Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li |
here |
| Graph Transformers on EHRs: Better Representation Improves Downstream Performance |
Raphael Poulain, Rahmatollah Beheshti |
here |
| Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning |
Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña-Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel Castro, Daniel Alexander |
here |
| GRAPH-CONSTRAINED DIFFUSION FOR END-TO-END PATH PLANNING |
DINGYUAN SHI, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye |
here |
| CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs |
Florian Grötschla, Joël Mathys, Róbert Veres, Roger Wattenhofer |
here |
| Universal Graph Random Features |
Isaac Reid, Krzysztof Choromanski, Eli Berger, Adrian Weller |
here |
| A Simple and Scalable Representation for Graph Generation |
Yunhui Jang, Seul Lee, Sungsoo Ahn |
here |
| Towards Foundation Models for Knowledge Graph Reasoning |
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu |
here |
| Training Graph Transformers via Curriculum-Enhanced Attention Distillation |
Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu |
here |
| Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors |
Hang Yin, Zihao Wang, Yangqiu Song |
here |
| Graph Metanetworks for Processing Diverse Neural Architectures |
Derek Lim, Haggai Maron, Marc T Law, Jonathan Lorraine, James Lucas |
here |
| Deceptive Fairness Attacks on Graphs via Meta Learning |
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong |
here |
| Graph Parsing Networks |
Yunchong Song, Siyuan Huang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin |
here |
| Conformal Inductive Graph Neural Networks |
Soroush H. Zargarbashi, Aleksandar Bojchevski |
here |
| Polynormer: Polynomial-Expressive Graph Transformer in Linear Time |
Chenhui Deng, Zichao Yue, Zhiru Zhang |
here |
| Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks |
Federico Errica, Mathias Niepert |
here |
| Efficient Subgraph GNNs by Learning Effective Selection Policies |
Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron |
here |
| DyVal: Graph-informed Dynamic Evaluation of Large Language Models |
Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Gong, Diyi Yang, Xing Xie |
here |
| PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks |
Junwei Su, Difan Zou, Chuan Wu |
here |
| One For All: Towards Training One Graph Model For All Classification Tasks |
Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang |
here |
| GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries |
Xiaoqi Wang, Han Wei Shen |
here |
| Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries |
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios |
here |
| iGraphMix: Input Graph Mixup Method for Node Classification |
Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon |
here |
| A Stochastic Centering Framework for Improving Calibration in Graph Neural Networks |
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan |
here |
| Deep Temporal Graph Clustering |
Meng Liu, Yue Liu, KE LIANG, Wenxuan Tu, Siwei Wang, sihang zhou, Xinwang Liu |
here |
| Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach |
Aoqi Zuo, yiqing li, Susan Wei, Mingming Gong |
here |
| A Generative Pre-Training Framework for Spatio-Temporal Graph Transfer Learning |
Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li |
here |
| Learning Multi-Agent Communication from Graph Modeling Perspective |
Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao |
here |
| Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs |
Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han |
here |
| From Matching to Mixing: A Graph Interpolation Approach for SAT Instance Generation |
Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan |
here |
| From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module |
Claudio Battiloro, Indro Spinelli, Lev Telyatinkov, Michael Bronstein, Simone Scardapane, Paolo Di Lorenzo |
here |
| Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values. |
Xiaodan Chen, Xiucheng Li, Bo Liu, Zhijun Li |
here |
| InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior |
Chenguo Lin, Yadong MU |
here |
| A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks |
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen |
here |
| HiGen: Hierarchical Graph Generative Networks |
Mahdi Karami |
here |
| Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-Image Generation |
Jaemin Cho, Yushi Hu, Jason Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang |
here |
| GraphGuard: Provably Robust Graph Classification against Adversarial Attacks |
Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia |
here |
| Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness |
Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang |
here |
| HoloNets: Spectral Convolutions do extend to Directed Graphs |
Christian Koke, Daniel Cremers |
here |
| Rethinking Label Poisoning for GNNs: Pitfalls and Attacks |
Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski |
here |
| Long-range Neural Atom Learning for Molecular Graphs |
Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han |
here |
| Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations |
Giovanni De Felice, Andrea Cini, Daniele Zambon, Vladimir Gusev, Cesare Alippi |
here |
| Complete and Efficient Graph Transformers for Crystal Material Property Prediction |
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
here |
| Forward Learning of Graph Neural Networks |
Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan Rossi, Puja Trivedi, Nesreen Ahmed |
here |
| Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks |
Kesen Zhao, Liang Zhang |
here |
| Local Graph Clustering with Noisy Labels |
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang |
here |
| Rethinking and Extending the Probabilistic Inference Capacity of GNNs |
Tuo Xu, Lei Zou |
here |
| Robust Angular Synchronization via Directed Graph Neural Networks |
Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu |
here |
| TEDDY: Trimming Edges with Degree-based Graph Diffusion Strategy |
Hyunjin Seo, Jihun Yun, Eunho Yang |
here |
| Locality-Aware Graph Rewiring in GNNs |
Federico Barbero, Ameya Velingker, Amin Saberi, Michael Bronstein, Francesco Di Giovanni |
here |
| Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection |
Xiangyu Dong, Xingyi Zhang, Sibo WANG |
here |
| BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics |
Suresh Bishnoi, Jayadeva Jayadeva, Sayan Ranu, N. M. Anoop Krishnan |
here |
| Efficient and Scalable Graph Generation through Iterative Local Expansion |
Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer |
here |
| GOAt: Explaining Graph Neural Networks via Graph Output Attribution |
Shengyao Lu, Keith G Mills, Jiao He, Bang Liu, Di Niu |
here |
| Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials |
Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram Deshpande |
here |
| A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs |
Thien Le, Luana Ruiz, Stefanie Jegelka |
here |
| Transformers vs. Message Passing GNNs: Distinguished in Uniform |
Jan Tönshoff, Eran Rosenbluth, Martin Ritzert, Berke Kisin, Martin Grohe |
here |
| Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision |
Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen |
here |
| LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference |
Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao |
here |
| Hypergraph Dynamic System |
Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao |
here |
| Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View |
YUJIE MO, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu |
here |
| Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs |
Milan Papez, Martin Rektoris, Tomáš Pevný, Vaclav Smidl |
here |
| Label-free Node Classification on Graphs with Large Language Models (LLMs) |
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang |
here |
| Mayfly: a Neural Data Structure for Graph Stream Summarization |
yuan feng, Yukun Cao, Hairu Wang, Xike Xie, S Kevin Zhou |
here |
| GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks |
Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer |
here |
| Adaptive Self-training Framework for Fine-grained Scene Graph Generation |
Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park |
here |
| Structural Fairness-aware Active Learning for Graph Neural Networks |
Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada |
here |
| Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network |
Tianze Luo, Zhanfeng Mo, Sinno Pan |
here |
| VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition |
Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu, Liming Zhai, Ziyu Jia, Yang Liu |
here |
| Online GNN Evaluation Under Test-time Graph Distribution Shifts |
Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan |
here |
| Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability |
Zehao Dong, Muhan Zhang, Philip Payne, Michael Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen |
here |
| Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach |
Christian Fabian, Kai Cui, Heinz Koeppl |
here |
| VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs |
Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin CUI, Muhan Zhang, Jure Leskovec |
here |
| Latent 3D Graph Diffusion |
Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen |
here |
| Graph Neural Networks for Learning Equivariant Representations of Neural Networks |
Miltiadis (Miltos) Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J Burghouts, Efstratios Gavves, Cees G Snoek, David Zhang |
here |
| Graph Generation with $K^2$-trees |
Yunhui Jang, Dongwoo Kim, Sungsoo Ahn |
here |
| M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering |
Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan |
here |
| NP-GL: Extending Power of Nature from Binary Problems to Real-World Graph Learning |
Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael Huang, Tong Geng |
here |
| Clifford Group Equivariant Simplicial Message Passing Networks |
Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré |
here |
| FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction |
Yuxing Tian, Yiyan Qi, Fan Guo |
here |
| MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy |
Yan Sun, Jicong Fan |
here |
| Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning |
Linhao Luo, Yuan-Fang Li, Reza Haffari, Shirui Pan |
here |
| Revisiting Link Prediction: a data perspective |
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang |
here |
| Mixture of Weak and Strong Experts on Graphs |
Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo |
here |
| VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections |
Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long |
here |
| Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks |
Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer, Michalis Vazirgiannis, Henrik Boström |
here |
| Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning |
Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi |
here |
| Mitigating Severe Robustness Degradation on Graphs |
Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang |
here |
| Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph |
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel Ni, Heung-Yeung Shum, Jian Guo |
here |
| Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models |
Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang |
here |
| Orbit-Equivariant Graph Neural Networks |
Matthew Morris, Bernardo Grau, Ian Horrocks |
here |
| Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning |
Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan |
here |
| Boosting Graph Anomaly Detection with Adaptive Message Passing |
Jingyan Chen, Guanghui Zhu, Chunfeng Yuan, Yihua Huang |
here |
| Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND |
Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay |
here |
| Temporal Generalization Estimation in Evolving Graphs |
Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang |
here |
| Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks |
Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker, Andrea Bertozzi, Jack Xin, Bao Wang |
here |
| InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes |
Jiawei Sun, Kailai Li, Ruoxin Chen, Jie LI, Chentao Wu, Yue Ding, Junchi Yan |
here |
| Graph Lottery Ticket Automated |
Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang |
here |
| Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning |
Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi |
here |
| Partitioning Message Passing for Graph Fraud Detection |
Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen |
here |
| Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data |
Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji |
here |
| On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters |
Matthias Lanzinger, Pablo Barcelo |
here |
| Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective |
Kuan Li, YiWen Chen, Yang Liu, Jin Wang, QING HE, Minhao Cheng, Xiang Ao |
here |
| A Topological Perspective on Demystifying GNN-Based Link Prediction Performance |
Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr |
here |
| Hybrid Directional Graph Neural Network for Molecules |
Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui, Yuan Qi, Furao Shen |
here |
| Mirage: Model-agnostic Graph Distillation for Graph Classification |
Mridul Gupta, Sahil Manchanda, HARIPRASAD KODAMANA, Sayan Ranu |
here |
| PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters |
Jingyu Chen, Runlin Lei, Zhewei Wei |
here |
| StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning |
Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang |
here |
| GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation |
Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen |
here |