This is the source code of IJCAI'23 paper "Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification".
This code requires the following:
- Python==3.7.15
- Pytorch==1.10.1
- Pytorch Geometric==2.0.4
- DGL==0.8.2
- Numpy==1.21.5
- Scikit-learn==1.0.2
- Scipy==1.7.3
Just run the script corresponding to the dataset you want. For instance:
bash scripts/amazon_train_0.4.sh
If you compare with, build on, or use aspects of this work, please cite the following:
@inproceedings{gong2023beyond,
title={Beyond Homophily: Robust Graph Anomaly Detection via Neural Sparsification},
author={Gong, Zheng and Wang, Guifeng and Sun, Ying and Liu, Qi and Ning, Yuting and Xiong, Hui and Jingyu Peng},
booktitle={Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI},
year={2023}
}