Samyu0304 / LiSA
Code for Mind the Label Shift of Augmentation-based Graph OOD generalization (LiSA) in CVPR 2023. LiSA is a model-agnostic Graph OOD framework.
☆16Updated last year
Alternatives and similar repositories for LiSA:
Users that are interested in LiSA are comparing it to the libraries listed below
- Ratioanle-aware Graph Contrastive Learning codebase☆39Updated last year
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆21Updated 4 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆20Updated last year
- code for kdd feasibiiity☆10Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆28Updated 7 months ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆29Updated last year
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆33Updated 2 years 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
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆25Updated last year
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆32Updated 2 months ago
- The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs☆24Updated 5 months ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆39Updated 3 weeks ago
- ☆50Updated 2 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆48Updated last year
- The official source code for "LTE4G: Long-Tail Experts for Graph Neural Networks" paper, accepted at CIKM 2022.☆38Updated 2 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated 10 months ago
- A generative one-for-all model for joint graph language modeling☆23Updated 2 months ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆37Updated last year
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆28Updated 2 months ago
- Pytorch implementation for ICLR24:"Online GNN Evaluation Under Test-Time Graph Distribution Shifts"☆15Updated 9 months ago
- papers of distilling Graph Neural Network☆21Updated 3 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆38Updated last year
- Code for SGDD☆23Updated last year
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated last year
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆34Updated last year
- PyGDA is a Python library for Graph Domain Adaptation☆21Updated last month
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆94Updated 10 months ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year