pygda-team / pygda
PyGDA is a Python library for Graph Domain Adaptation
☆23Updated 2 months ago
Alternatives and similar repositories for pygda:
Users that are interested in pygda are comparing it to the libraries listed below
- ☆53Updated 3 months ago
- [NeurIPS 2023] The official implementation of "Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition…☆12Updated 7 months ago
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆28Updated 3 months ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆16Updated last year
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆36Updated last year
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆49Updated 2 years ago
- Rethinking Propagation for Unsupervised Graph Domain Adaptation☆12Updated 7 months ago
- code for kdd feasibiiity☆10Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆29Updated last year
- Published papers focusing on graph domain adaptation☆35Updated 2 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆29Updated 8 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆33Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆21Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆44Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆37Updated last year
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆23Updated last week
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated 11 months ago
- ☆15Updated last year
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆34Updated 7 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated 11 months ago
- A curated list of papers on graph transfer learning (GTL).☆16Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- ☆12Updated last year
- [Neurips 2024] Disentangled Graph Homophily☆21Updated last month
- Awesome Graph Condensation Papers☆33Updated 2 weeks ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆42Updated 2 years ago
- Code for "Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization (EAGLE)"☆21Updated last year
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆10Updated 4 months ago
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year