ispamm / MATELinks
MetA-Train to Explain
☆18Updated 3 years ago
Alternatives and similar repositories for MATE
Users that are interested in MATE are comparing it to the libraries listed below
Sorting:
- ☆18Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 5 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆23Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- ☆41Updated 3 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆48Updated last year
- Graph Structured Neural Network☆40Updated 3 years ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 4 years ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆44Updated 3 years ago
- Gradient gating (ICLR 2023)☆55Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 3 years ago
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆28Updated 3 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆36Updated 2 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆71Updated 9 months ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆84Updated 2 years ago
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆53Updated 2 years ago
- ☆57Updated 4 years ago
- Size-Invariant Graph Representations for Graph Classification Extrapolations (ICML 2021 Long Talk)☆23Updated 2 years ago
- Official Code of Decoupled Graph Convolution (DGC)☆16Updated 4 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 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
- Official repository of "On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs", CIKM 2022☆18Updated 3 years ago
- ☆30Updated 4 years ago
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆30Updated 4 years ago
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆16Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆92Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆42Updated 4 years ago