BUPT-GAMMA / CaGCNLinks
This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".
☆22Updated 4 years ago
Alternatives and similar repositories for CaGCN
Users that are interested in CaGCN are comparing it to the libraries listed below
Sorting:
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆97Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆121Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- ☆14Updated 3 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆83Updated 4 years ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 4 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆46Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆38Updated 3 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Updated 2 years ago
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆131Updated 2 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆92Updated 4 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆23Updated 2 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Updated last year
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Updated 3 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆63Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆28Updated 3 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 2 years ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago