kaize0409 / awesome-graph-data-augmentaionLinks
A curated list of publications and code about data augmentaion for graphs.
☆63Updated 3 years ago
Alternatives and similar repositories for awesome-graph-data-augmentaion
Users that are interested in awesome-graph-data-augmentaion are comparing it to the libraries listed below
Sorting:
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆84Updated 2 years ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆131Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆82Updated 4 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- NeurIPS 2022 - SHGP☆32Updated 2 years ago
- Code for paper https://arxiv.org/abs/2102.13186☆42Updated 4 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 3 years ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆59Updated 4 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆107Updated 6 months ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 3 years ago
- Deep Graph Outlier Detection☆67Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆46Updated 3 years ago
- ☆28Updated 4 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆92Updated 4 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆68Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆62Updated 3 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 4 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆138Updated 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
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆91Updated last year
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- Paper List for Fair Graph Learning (FairGL).☆144Updated last year
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆77Updated 3 years ago