BUPT-GAMMA / CaGCNLinks
This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".
☆22Updated 3 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"☆60Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 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
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated last year
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆43Updated 2 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆53Updated 2 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
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆104Updated 2 months ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆38Updated 2 years ago
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 3 years ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆24Updated 2 months ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆27Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆21Updated 9 months ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆89Updated 3 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆89Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago