/Bagel

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Primary LanguagePython

Bagel

The implementation of 'Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder' Models are in model.py.

Dependencies

python >= 3.7

pip install -r requirements.txt

Run

python main.py

Citation

Li, Zeyan, Wenxiao Chen, and Dan Pei. "Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder." 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC). IEEE, 2018.

@inproceedings{li2018robust,
  title={Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder},
  author={Li, Zeyan and Chen, Wenxiao and Pei, Dan},
  booktitle={2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC)},
  pages={1--9},
  year={2018},
  organization={IEEE}
}