yongduosui / AIA
[NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He.
☆16Updated last year
Alternatives and similar repositories for AIA:
Users that are interested in AIA are comparing it to the libraries listed below
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆28Updated 4 months ago
- The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs☆26Updated 7 months ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆50Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆32Updated 4 months ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆10Updated 4 months ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆42Updated 2 months ago
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆36Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆28Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆40Updated last year
- ☆18Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆30Updated 9 months ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆29Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- A curated list of papers on graph transfer learning (GTL).☆16Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆38Updated 2 years ago
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆20Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated 11 months ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- PyGDA is a Python library for Graph Domain Adaptation☆24Updated last week
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆24Updated last month
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- Pytorch implementation of EvenNet.☆19Updated 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- code for kdd feasibiiity☆10Updated last year