# GCN_AnomalyDetection

**Repository Path**: yangxubbc/GCN_AnomalyDetection

## Basic Information

- **Project Name**: GCN_AnomalyDetection
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-09-02
- **Last Updated**: 2025-09-02

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

Deep Anomaly Detection on Attributed Networks(SDM2019)
============

## Dominant

This is the source code of paper "[Deep Anomaly Detection on Attributed Networks](http://www.public.asu.edu/~kding9/pdf/SDM2019_Deep.pdf)". A new PyTorch version can be accessed from https://github.com/kaize0409/GCN_AnomalyDetection_pytorch

![The proposed framework](framework.png)

## Requirements
python==2.7.3

tensorflow>=1.1.0

## Usage
```python run.py```

## Cite

Please cite our paper if you use this code in your own work:

```
@inproceedings{ding2019deep,
  title={Deep Anomaly Detection on Attributed Networks},
  author={Ding, Kaize and Li, Jundong and Bhanushali, Rohit and Liu, Huan},
  booktitle={SIAM International Conference on Data Mining (SDM)},
  year={2019}
}
```
## Update

A new PyTorch version of the code can be accessed from https://github.com/kaize0409/GCN_AnomalyDetection_pytorch