graph classification

Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks NeurIPS 2023 Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees AAAI 2023 A Simple yet Effective Method for Graph Classification IJCAI 2022 Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs AAAI 2022 Boosting Graph Structure Learning with Dummy Nodes ICML 2022 Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats NeurIPS 2022 CGLB: Benchmark Tasks for Continual Graph Learning NeurIPS 2022 Convergent Graph Solvers ICLR 2022 Cross-Domain Few-Shot Graph Classification AAAI 2022 Data-Free Adversarial Knowledge Distillation for Graph Neural Networks IJCAI 2022 Differentially Describing Groups of Graphs AAAI 2022 FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs IJCAI 2022 Filtration-Enhanced Graph Transformation IJCAI 2022 Generalization Analysis of Message Passing Neural Networks on Large Random Graphs NeurIPS 2022 G-Mixup: Graph Data Augmentation for Graph Classification ICML 2022 GraphDIVE: Graph Classification by Mixture of Diverse Experts IJCAI 2022 Graph Filtration Kernels AAAI 2022 Graph Neural Architecture Search Under Distribution Shifts ICML 2022 GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NeurIPS 2022 Graph Scattering beyond Wavelet Shackles NeurIPS 2022 Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation AAAI 2022 High-Order Pooling for Graph Neural Networks with Tensor Decomposition NeurIPS 2022 KerGNNs: Interpretable Graph Neural Networks with Graph Kernels AAAI 2022 Label-invariant Augmentation for Semi-Supervised Graph Classification NeurIPS 2022 Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NeurIPS 2022