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Counterfactual Graph Learning for Anomaly Detection on Attributed Networks, IEEE TKDE 2023

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Counterfactual Graph Learning for Anomaly Detection on Attributed Networks

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

Citation

@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},
}

Data

  • The data is in directory graphs.

Dependencies

Run the following command to install dependencies with Anaconda virtual environment:

conda create -n cfad python==3.9

pip install -r requirements.txt

Run

# PubMed
python run.py

Description of hyper-parameters can be found in run.py.

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Counterfactual Graph Learning for Anomaly Detection on Attributed Networks, IEEE TKDE 2023

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