graph kernel

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NeurIPS 2022 KerGNNs: Interpretable Graph Neural Networks with Graph Kernels AAAI 2022 Non-separable Spatio-temporal Graph Kernels via SPDEs AISTATS 2022 TGNN: A Joint Semi-supervised Framework for Graph-level Classification IJCAI 2022 Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NeurIPS 2022 Weisfeiler-Lehman Meets Gromov-Wasserstein ICML 2022 An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk ACML 2021 Deep Graph Spectral Evolution Networks for Graph Topological Evolution AAAI 2021 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels ICLR 2021 Isolation Graph Kernel AAAI 2021 Structure-Aware Random Fourier Kernel for Graphs NeurIPS 2021 Convolutional Kernel Networks for Graph-Structured Data ICML 2020 GraKeL: A Graph Kernel Library in Python JMLR 2020 Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification AAAI 2020 Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings NeurIPS 2020 A Persistent Weisfeiler-Lehman Procedure for Graph Classification ICML 2019 A Similarity Measurement Method Based on Graph Kernel for Disconnected Graphs IJCAI 2019 GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks IJCAI 2019 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels NeurIPS 2019 Rethinking Kernel Methods for Node Representation Learning on Graphs NeurIPS 2019 Wasserstein Weisfeiler-Lehman Graph Kernels NeurIPS 2019 A Degeneracy Framework for Graph Similarity IJCAI 2018 Anonymous Walk Embeddings ICML 2018 A Property Testing Framework for the Theoretical Expressivity of Graph Kernels IJCAI 2018 RetGK: Graph Kernels based on Return Probabilities of Random Walks NeurIPS 2018