nerdslab / bgrlLinks
PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
☆81Updated last year
Alternatives and similar repositories for bgrl
Users that are interested in bgrl are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 11 months ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆60Updated 2 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆114Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆104Updated 2 months ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆76Updated 3 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆140Updated 9 months ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆89Updated 3 years ago
- ☆135Updated 2 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆92Updated 10 months ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL☆35Updated 7 months ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- ☆77Updated 4 years ago
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆45Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 4 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 3 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆65Updated last year
- Papers about developing DL methods on disassortative graphs☆48Updated 3 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆168Updated last year
- ☆57Updated 3 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago