StackVAE-G: An efficient and interpretable model for time series anomaly detection

StackVAE-G: An efficient and interpretable model for time series anomaly detection

Recent studies have shown that autoencoder-based models can achieve superior performance on anomaly detection tasks due to their excellent ability to fit complex data in an unsupervised manner. In this work, we propose a novel autoencoder-based model, named StackVAE-G that can significantly bring th...

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Bibliographic Details
Main Authors: Wenkai Li, Wenbo Hu, Ting Chen, Ning Chen, Cheng Feng
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2022-01-01
Series:AI Open
Subjects:
Time-series
Anomaly detection
Autoencoders
Graph neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2666651022000110

Internet

http://www.sciencedirect.com/science/article/pii/S2666651022000110

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