graph classification

Multi-Channel Graph Neural Networks IJCAI 2020 Neighbor Combinatorial Attention for Critical Structure Mining IJCAI 2020 Path Integral Based Convolution and Pooling for Graph Neural Networks NeurIPS 2020 PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures AISTATS 2020 Probabilistic Learning on Graphs via Contextual Architectures JMLR 2020 Random Walk Graph Neural Networks NeurIPS 2020 Rep the Set: Neural Networks for Learning Set Representations AISTATS 2020 Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs NeurIPS 2020 Universal Function Approximation on Graphs NeurIPS 2020 Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings NeurIPS 2020 Adversarial Examples for Graph Data: Deep Insights into Attack and Defense IJCAI 2019 A Persistent Weisfeiler-Lehman Procedure for Graph Classification ICML 2019 AttPool: Towards Hierarchical Feature Representation in Graph Convolutional Networks via Attention Mechanism ICCV 2019 Gaussian-Induced Convolution for Graphs AAAI 2019 Geometric Scattering for Graph Data Analysis ICML 2019 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels NeurIPS 2019 Learning metrics for persistence-based summaries and applications for graph classification NeurIPS 2019 Optimal Transport for structured data with application on graphs ICML 2019 Relational Pooling for Graph Representations ICML 2019 Self-Attention Graph Pooling ICML 2019 Understanding Attention and Generalization in Graph Neural Networks NeurIPS 2019 Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity IJCAI 2019 Wasserstein Weisfeiler-Lehman Graph Kernels NeurIPS 2019 Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks AAAI 2019 A Degeneracy Framework for Graph Similarity IJCAI 2018