snap-stanford / GIB
Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
☆123Updated last year
Related projects: ⓘ
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆115Updated 2 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆96Updated 2 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆82Updated 2 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆109Updated 4 years ago
- ☆128Updated last year
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆42Updated 2 years ago
- How Powerful are Spectral Graph Neural Networks☆70Updated last year
- ☆57Updated last year
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆108Updated last week
- ☆72Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆90Updated 6 months ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆79Updated last year
- ☆29Updated 4 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆97Updated last year
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆57Updated 3 years ago
- Official implementation of our FLAG paper (CVPR2022)☆139Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆80Updated last year
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆72Updated 3 years ago
- ☆94Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆56Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆85Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆74Updated 3 years ago
- ☆60Updated 3 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆111Updated 2 years ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆49Updated last year
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆94Updated last year
- Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)☆98Updated 2 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆119Updated last month
- Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL☆35Updated last year