train.py puts all of the above together and may be used to execute a full training run.
@inproceedings{jin2023local, title={Local-global defense against unsupervised adversarial attacks on graphs}, author={Jin, Di and Feng, Bingdao and Guo, Siqi and Wang, Xiaobao and Wei, Jianguo and Wang, Zhen}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, volume={37}, number={7}, pages={8105--8113}, year={2023} }