amazon-science / doscondLinks
☆19Updated 2 years ago
Alternatives and similar repositories for doscond
Users that are interested in doscond are comparing it to the libraries listed below
Sorting:
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆118Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆45Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆29Updated 3 years ago
- code for kdd feasibiiity☆12Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Code for SGDD☆26Updated 2 years ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated 2 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
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆34Updated last year
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Updated last year
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆40Updated 2 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆47Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 3 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 3 years ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 2 months ago
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆84Updated 2 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated 2 years ago
- [CIKM 2023 Short] Code for the paper "S-Mixup: Structural Mixup for Graph Neural Networks"☆18Updated 2 years ago
- A curated list of resources for OOD detection with graph data.☆19Updated last year
- 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
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆57Updated last year
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆44Updated 2 years ago