ispamm / MATE
MetA-Train to Explain
☆15Updated 2 years ago
Related projects: ⓘ
- ☆26Updated 7 months ago
- ☆30Updated last year
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆50Updated last year
- ☆25Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆74Updated 2 years ago
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆85Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆45Updated 3 years ago
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆27Updated 2 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆40Updated 3 years ago
- ☆15Updated 9 months ago
- Graph Structured Neural Network☆38Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- Gradient gating (ICLR 2023)☆51Updated last year
- Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR …☆34Updated last month
- ☆13Updated this week
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆82Updated 2 years ago
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆39Updated 3 years ago
- ☆35Updated last year
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆73Updated 3 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆79Updated last year
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆37Updated last year
- ☆54Updated 2 years ago
- Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"☆53Updated 3 years ago
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆22Updated 2 years ago
- ☆25Updated 4 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆64Updated 2 years ago
- Code and dataset to test empirically the expressive power of graph pooling operators.☆31Updated 10 months ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆47Updated 2 years ago
- ☆24Updated 3 years ago