GRM

This repository contains the data release for the paper Generative Risk Minimization for Out-of-Distribution Generalization on Graphs, published in TMLR 2025.

Requirement:

torch==1.8.1

Code Running:

Run the command: unzip data.zip

Then run the command: python mainl2aug.py

To switch the dataset, modify the "datasets" value in parse.py.

The dataset directory should also be specified in parse.py.

Questions

If you encounter any cases and need help, feel free to contact sw3wv@virginia.edu. We are more than willing to help!

Citation

If you find our work helpful, please kindly consider citing our paper. Thank you so much for your attention!

@article{wang2025generative,
  title={Generative Risk Minimization for Out-of-Distribution Generalization on Graphs},
  author={Wang, Song and Tan, Zhen and Zhu, Yaochen and Zhang, Chuxu and Li, Jundong},
  journal={TMLR},
  year={2025}
}