A comparison of classical and variational autoencoders for anomaly detection

Patuzzo, Fabrizio (2020) A comparison of classical and variational autoencoders for anomaly detection. Technical Report arxiv , Manno.

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Abstract

This paper analyzes and compares a classical and a variational autoencoder in the context of anomaly detection. To better understand their architecture and functioning, describe their properties and compare their performance, it explores how they address a simple problem: reconstructing a line with a slope.

Item Type:	Report (Technical Report)
Subjects:	Computer sciences > Artificial intelligence > Computer vision Computer sciences > Artificial intelligence > Machine learning
Department/unit:	Dipartimento tecnologie innovative > Istituto Dalle Molle di studi sull'intelligenza artificiale
Depositing User:	Fabrizio Patuzzo
Date Deposited:	08 Oct 2020 13:33
Last Modified:	08 Oct 2020 13:33
URI:	http://repository.supsi.ch/id/eprint/11987

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