LFhase / GMTLinks
[ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?
☆15Updated last year
Alternatives and similar repositories for GMT
Users that are interested in GMT are comparing it to the libraries listed below
Sorting:
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Updated last year
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆24Updated 2 years ago
- ☆14Updated 3 years ago
- The open source code for ICDM2022 paper "Unifying Graph Contrastive Learning with Flexible Contextual Scopes"☆21Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆62Updated 2 years ago
- Codes for Paper: From Hypergraph Energy Functions to Hypergraph Neural Networks☆23Updated 2 years ago
- Graph Transformers for Large Graphs☆22Updated last year
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products (ICML 2024)☆10Updated last year
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated 2 years ago
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆117Updated 2 years ago
- The official Implementation for TKDE paper "Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalizatio…☆14Updated 2 years ago
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆102Updated last year
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 months ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Updated last year
- PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))☆17Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".☆91Updated last year
- [ICLR'25 Spotlight] Revisiting Random Walks for Learning on Graphs (RWNN), in PyTorch☆16Updated 8 months ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 2 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- DHG-Bench is a comprehensive benchmark for Deep Hypergraph Learning☆20Updated last month
- ☆29Updated 3 years ago
- Official implementation of GOAT model (ICML2023)☆38Updated 2 years ago
- The official source code for "Shift-Robust Molecular Relational Learning with Causal Substructure"☆24Updated 2 years ago