MST-VAE: Multi-Scale Temporal Variational Autoencoder for Anomaly Detection in Multivariate Time Series

In IT monitoring systems, anomaly detection plays a vital role in detecting and alerting unexpected behaviors timely to system operators. With the growth of signal data in both volumes and dimensions during operation, unsupervised learning turns out to be a great solution to trigger anomalies thanks...

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Bibliografische gegevens

Hoofdauteurs:	Tuan-Anh Pham, Jong-Hoon Lee, Choong-Shik Park
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2022-10-01
Reeks:	Applied Sciences
Onderwerpen:	multi-scale convolutional kernels variational autoencoder multivariate time series anomaly detection convolutional neural network
Online toegang:	https://www.mdpi.com/2076-3417/12/19/10078
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