cshjin / GCLLinks
List of Publications in Graph Contrastive Learning
☆35Updated 3 years ago
Alternatives and similar repositories for GCL
Users that are interested in GCL are comparing it to the libraries listed below
Sorting:
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 3 years ago
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated last year
- Collection of resources related with Graph Contrastive Learning.☆34Updated 4 years ago
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 4 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆46Updated 3 years ago
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆58Updated 5 years ago
- Contrastive Graph Structure Learning via Information Bottleneck for Recommendation☆29Updated 2 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆58Updated last year
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆110Updated 3 years ago
- SCR: Training Graph Neural Networks with Consistency Regularization☆37Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- A collection of graph contrastive learning methods.☆18Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- source code of KDD 2021 paper "Pre-training on Large-Scale Heterogeneous Graph".☆22Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL☆35Updated 4 months ago
- [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision☆157Updated 2 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 4 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆36Updated 4 years ago
- ☆11Updated 4 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆116Updated 5 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago
- Facilitating learning, using, and designing graph processing pipelines/models systematically.☆27Updated 3 years ago
- ☆42Updated last year
- Implementation for Simple Spectral Graph Convolution in ICLR 2021☆83Updated 2 years ago
- Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".☆55Updated 3 years ago
- ☆96Updated 4 years ago
- [KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks☆30Updated 3 years ago