ha-lins / PGCLLinks
The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]
☆24Updated 3 years ago
Alternatives and similar repositories for PGCL
Users that are interested in PGCL are comparing it to the libraries listed below
Sorting:
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 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
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆21Updated 9 months ago
- source code of IJCAI 2021 paper "Graph Representation with Curriculum Contrastive Learning"☆26Updated 4 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated 2 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆92Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆45Updated 3 years ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Updated last year
- ☆55Updated 2 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆24Updated 2 years ago
- Official PyTorch implementation for the following KDD2022 paper: Variational Inference for Training Graph Neural Networks in Low-Data Re…☆20Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆60Updated 2 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆88Updated 10 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- Collection of resources related with Graph Contrastive Learning.☆34Updated 4 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆24Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- [IJCAI 2023] Graph Propagation Transformer for Graph Representation Learning☆49Updated last year
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆76Updated 3 years ago