Science Score: 23.0%
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Repository
usad
Basic Info
- Host: GitHub
- Owner: CSTCloudOps
- License: other
- Default Branch: master
- Size: 2.8 MB
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· Last pushed over 4 years ago
https://github.com/CSTCloudOps/usad/blob/master/
# USAD - UnSupervised Anomaly Detection on multivariate time series
Scripts and utility programs for implementing the USAD architecture.
Implementation by: Francesco Galati.
Additional contributions: Julien Audibert, Maria A. Zuluaga.
## How to cite
If you use this software, please cite the following paper as appropriate:
Audibert, J., Michiardi, P., Guyard, F., Marti, S., Zuluaga, M. A. (2020).
USAD : UnSupervised Anomaly Detection on multivariate time series.
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, August 23-27, 2020
## Requirements
* PyTorch 1.6.0
* CUDA 10.1 (to allow use of GPU, not compulsory)
## Running the Software
All the python classes and functions strictly needed to implement the USAD architecture can be found in `usad.py`.
An example of an application deployed with the [SWaT dataset] is included in `USAD.ipynb`.
## Copyright and licensing
Copyright 2020 Eurecom.
This software is released under the BSD-3 license. Please see the license file_ for details.
## Publication
Audibert et al. [USAD : UnSupervised Anomaly Detection on multivariate time series]. 2020
[SWaT dataset]: https://itrust.sutd.edu.sg/itrust-labs_datasets/dataset_info/#swat
[USAD : UnSupervised Anomaly Detection on multivariate time series]: https://dl.acm.org/doi/pdf/10.1145/3394486.3403392
Owner
- Name: CSTCloud Lab
- Login: CSTCloudOps
- Kind: organization
- Location: China
- Website: https://www.cstcloud.cn
- Repositories: 20
- Profile: https://github.com/CSTCloudOps