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Graph Neural Networks

1127 directly classified papers

Papers per year

Papers

Optimality of Message-Passing Architectures for Sparse Graphs NIPS 2023
Maximum Independent Set: Self-Training through Dynamic Programming NIPS 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphops NIPS 2023
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem NIPS 2023
Graph Contrastive Learning with Stable and Scalable Spectral Encoding NIPS 2023
Fine-grained Expressivity of Graph Neural Networks NIPS 2023
Transformers over Directed Acyclic Graphs NIPS 2023
Boosting Graph Structure Learning with Dummy Nodes ICML 2022
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders NIPS 2022
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs NIPS 2022
Graph Scattering beyond Wavelet Shackles NIPS 2022
ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery NIPS 2022
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias NIPS 2022
Parameter-free Dynamic Graph Embedding for Link Prediction NIPS 2022
Simplified Graph Convolution with Heterophily NIPS 2022
Learning Physical Dynamics with Subequivariant Graph Neural Networks NIPS 2022
Long Range Graph Benchmark NIPS 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NIPS 2022
MGNNI: Multiscale Graph Neural Networks with Implicit Layers NIPS 2022
Hierarchical Graph Transformer with Adaptive Node Sampling NIPS 2022
Graph Neural Networks are Dynamic Programmers NIPS 2022
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NIPS 2022
SHINE: SubHypergraph Inductive Neural nEtwork NIPS 2022
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily ICML 2022
Simultaneous Graph Signal Clustering and Graph Learning ICML 2022