During 6.24-6.26, I scanned the accepted paper lists of ICML 2019, KDD 2019, and IJCAI 2019, and searched for paper titles containing the graph keyword by Google. I selected many interesting and reachable papers as below, then marked papers related to my research topics as + symbol, and irrelevant ones as - symbol.
- + Self-Attention Graph Pooling
- + Graph U-Nets
- + Adversarial Attacks on Node Embeddings via Graph Poisoning
- - Simplifying Graph Convolutional Networks
- + MixHop: High-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
- + Position-aware Graph Neural Networks
- + Relational Pooling for Graph Representations
- - Disentangled Graph Convolutional Network
- - Learning Discrete Structures for Graph Neural Networks
- - Stochastic Blockmodels meet Graph Neural Networks
- + Graphite: Iterative Generative Modeling of Graphs
- - Ego-CNN: Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
- + Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
- + Spectral Clustering of Signed Graphs via Matrix Power Means
- + Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
- + A Representation Learning Framework for Property Graphs
- - Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
- + DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
- + Estimating Graphlet Statistics via Lifting
- + Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
- + Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach
- + Graph Recurrent Networks with Attributed Random Walks
- - Graph Representation Learning via Hard and Channel-Wise Attention Networks
- - Graph-based Semi-Supervised & Active Learning for Edge Flows
- - Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
- + Learning Dynamic Context Graphs for Predicting Social Events
- + NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching
- + Predicting Path Failure In Time-Evolving Graphs
- + Robust Graph Convolutional Networks Against Adversarial Attacks
- + Scalable Graph Embeddings via Sparse Transpose Proximities
- - Stability and Generalization of Graph Convolutional Neural Networks
- - Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat
- - Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
- - OAG: Toward Linking Large-scale Heterogeneous Entity Graphs
- + A Degeneracy Framework for Scalable Graph Autoencoders
- + Adversarial Examples on Graph Data: Deep Insights into Attack and Defense
- + Attributed Graph Clustering via Adaptive Graph Convolution
- + Attributed Graph Clustering: A Deep Attentional Embedding Approach
- - Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
- + Fairwalk: Towards Fair Graph Embedding
- - Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
- + GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks
- + Graph WaveNet for Deep Spatial-Temporal Graph Modeling
- + Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification
- - Large Scale Evolving Graphs with Burst Detection
- + MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
- - Multi-view Knowledge Graph Embedding for Entity Alignment
- + Node Embedding over Temporal Graphs
- - Semi-supervised User Profiling with Heterogeneous Graph Attention Networks
- + SPAGAN: Shortest Path Graph Attention Network
- - Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
- + Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering
- - Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
- + STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems