graph isomorphism

A Practical, Progressively-Expressive GNN NeurIPS 2022 Going Deeper into Permutation-Sensitive Graph Neural Networks ICML 2022 Graph Filtration Kernels AAAI 2022 How Powerful are Spectral Graph Neural Networks ICML 2022 PF-GNN: Differentiable particle filtering based approximation of universal graph representations ICLR 2022 Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NeurIPS 2022 Weisfeiler-Lehman Meets Gromov-Wasserstein ICML 2022 Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective ICLR 2021 Identity-aware Graph Neural Networks AAAI 2021 Impossibility of Partial Recovery in the Graph Alignment Problem COLT 2021 On Graph Neural Networks versus Graph-Augmented MLPs ICLR 2021 Replicating and Extending “Because Their Treebanks Leak”: Graph Isomorphism, Covariants, and Parser Performance ACL 2021 The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs IJCAI 2021 The Surprising Power of Graph Neural Networks with Random Node Initialization IJCAI 2021 A Learning Based Branch and Bound for Maximum Common Subgraph Related Problems AAAI 2020 A Novel Higher-order Weisfeiler-Lehman Graph Convolution ACML 2020 Graph Random Neural Features for Distance-Preserving Graph Representations ICML 2020 How hard is to distinguish graphs with graph neural networks? NeurIPS 2020 L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks CVPR 2020 Principal Neighbourhood Aggregation for Graph Nets NeurIPS 2020 Some Languages Seem Easier to Parse Because Their Treebanks Leak EMNLP 2020 The Logical Expressiveness of Graph Neural Networks ICLR 2020 Universal Function Approximation on Graphs NeurIPS 2020 Deanonymizing Social Networks Using Structural Information IJCAI 2019 How Powerful are Graph Neural Networks? ICLR 2019