This is a repository hosting the code of our paper: Counterfactual Graph Learning for Anomaly Detection on Attributed Networks, IEEE Transactions on Knowledge and Data Engineering, 2023, 35(10):10540 - 10553. https://ieeexplore.ieee.org/abstract/document/10056298
@article{xiao2023counterfactual,
author={Xiao, Chunjing and Xu, Xovee and Lei, Yue and Zhang, Kunpeng and Liu, Siyuan and Zhou, Fan},
journal={IEEE Transactions on Knowledge and Data Engineering},
title={Counterfactual Graph Learning for Anomaly Detection on Attributed Networks},
year={2023},
volume={35},
number={10},
pages={10540-10553},
}
- The data is in directory graphs.
Run the following command to install dependencies with Anaconda virtual environment:
conda create -n cfad python==3.9
pip install -r requirements.txt
# PubMed
python run.py
Description of hyper-parameters can be found in run.py
.