weisfeiler-lehman test

LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation AAAI 2026 Spectral Basis Learning for Expressive Graph Neural Networks in Link Prediction AAAI 2026 Towards a Complete Logical Framework for GNN Expressiveness ICLR 2025 Efficient Subgraph GNNs by Learning Effective Selection Policies ICLR 2024 G^2N^2 : Weisfeiler and Lehman go grammatical ICLR 2024 Non-convolutional graph neural networks. NeurIPS 2024 On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers AISTATS 2024 Rethinking and Extending the Probabilistic Inference Capacity of GNNs ICLR 2024 Spatio-Spectral Graph Neural Networks NeurIPS 2024 Union Subgraph Neural Networks AAAI 2024 Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes AAAI 2024 A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests ICML 2023 A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models ACML 2023 Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman NeurIPS 2023 Going beyond persistent homology using persistent homology NeurIPS 2023 Local Vertex Colouring Graph Neural Networks ICML 2023 Non-IID Transfer Learning on Graphs AAAI 2023 On the Expressive Power of Geometric Graph Neural Networks ICML 2023 Probing Graph Representations AISTATS 2023 Rethinking the Expressive Power of GNNs via Graph Biconnectivity ICLR 2023 Three Iterations of (d − 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points NeurIPS 2023 Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees AAAI 2023 A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?" ICLR 2022 Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks NeurIPS 2022 From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness ICLR 2022