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:
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 3 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 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"☆81Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆61Updated 2 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆82Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 3 months ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆59Updated 4 years ago
- Code for paper https://arxiv.org/abs/2102.13186☆43Updated 4 years ago
- NeurIPS 2022 - SHGP☆31Updated 2 years ago
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆54Updated 2 years ago
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 11 months ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆131Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 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 3 years ago
- Paper List for Fair Graph Learning (FairGL).☆142Updated last year
- Source code of "IJCAI20 - Network Schema Preserving Heterogeneous Information Network Embedding"☆25Updated 4 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆90Updated 3 years ago
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆44Updated 3 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆60Updated 2 years ago
- The source code of HeCo☆168Updated 3 years ago
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆39Updated last year
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆25Updated 7 months ago