PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
-
Updated
Jan 16, 2024 - Python
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
Implementation of MTAD-GAT: Multivariate Time-series Anomaly Detection via Graph Attention Network
IDPS-ESCAPE (Intrusion Detection and Prevention Systems for Evading Supply Chain Attacks and Post-compromise Effects), part of the CyFORT project: open-source SOAR system powered by a dedicated ML-based anomaly detection toolbox (ADBox) integrated with open-source software such as Wazuh and Suricata.
MLflow version of MTAD-GAT
Add a description, image, and links to the mtad-gat topic page so that developers can more easily learn about it.
To associate your repository with the mtad-gat topic, visit your repo's landing page and select "manage topics."