ha-lins / PGCL
The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]
☆24Updated 2 years ago
Alternatives and similar repositories for PGCL:
Users that are interested in PGCL are comparing it to the libraries listed below
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆23Updated last year
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆59Updated 2 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆19Updated 5 months ago
- source code of IJCAI 2021 paper "Graph Representation with Curriculum Contrastive Learning"☆26Updated 3 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆45Updated 3 years ago
- [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".☆40Updated 2 years ago
- Pytorch implementation of WWW'23:"Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs"☆15Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆80Updated 3 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆41Updated last year
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆34Updated 2 years ago
- Official PyTorch implementation for the following KDD2022 paper: Variational Inference for Training Graph Neural Networks in Low-Data Re…☆19Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 10 months ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆88Updated last year
- Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)☆23Updated 2 years ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆21Updated 7 months ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆39Updated 2 years ago
- ☆15Updated 2 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆35Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 2 years ago
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆22Updated last year
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 10 months ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆51Updated 2 years ago
- Graph based Knowledge Distillation: A Survey☆66Updated last year
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆75Updated 3 years ago