How Dense Autoencoders can still Achieve the State-of-the-art in Time-Series Anomaly Detection

Louis Jensen, Jayme Fosa, Ben Teitelbaum, Peter Chin. How Dense Autoencoders can still Achieve the State-of-the-art in Time-Series Anomaly Detection. In M. Arif Wani, Ishwar K. Sethi, Weisong Shi, Guangzhi Qu, Daniela Stan Raicu, Ruoming Jin, editors, 20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021, Pasadena, CA, USA, December 13-16, 2021. pages 1272-1277, IEEE, 2021. [doi]

Abstract

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