lxiaorui / ElasticGNNLinks
Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
☆41Updated 3 years ago
Alternatives and similar repositories for ElasticGNN
Users that are interested in ElasticGNN are comparing it to the libraries listed below
Sorting:
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- ☆20Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 4 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL☆35Updated 4 months ago
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 2 years ago
- Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021☆41Updated 3 years ago
- Code for the papers: "Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach", "A Meta-Learning Approach for Gra…☆18Updated 3 years ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 2 years ago
- ☆57Updated 3 years ago
- Bags of Tricks in OGB (node classification) with GCNs.☆37Updated 3 years ago
- ☆37Updated 3 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆80Updated 3 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 2 years ago
- Official Code of Decoupled Graph Convolution (DGC)☆16Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- CIKM 2021: Pooling Architecture Search for Graph Classification☆20Updated 2 years ago
- ☆10Updated 3 years ago
- ☆62Updated 4 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago