Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection

Guangyao Zhang; Xin Gao; Lei Wang; Bing Xue; Shiyuan Fu; Jiahao Yu; Zijian Huang; Xu Huang

doi:10.1007/s10489-022-04324-3

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Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection

Guangyao Zhang Xin Gao Lei Wang Bing Xue Shiyuan Fu Jiahao Yu Zijian Huang Xu Huang

Year: 2022 Journal: Applied Intelligence Vol: 53 (12)Pages: 15855-15872 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-04324-3

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Keywords:

Computer science Anomaly detection Autoencoder Multivariate statistics Probabilistic logic Anomaly (physics) Artificial intelligence Series (stratigraphy) Pattern recognition (psychology) Time series Feature (linguistics) Scale (ratio) Feature extraction Data mining Artificial neural network Machine learning Geology

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection

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