Autoencoders

Dor Bank (), Noam Koenigstein () and Raja Giryes ()
Additional contact information
Dor Bank: Tel Aviv University, School of Electrical Engineering
Noam Koenigstein: Tel Aviv University, Department of Industrial Engineering, Faculty of Engineering
Raja Giryes: Tel Aviv University, School of Electrical Engineering

A chapter in Machine Learning for Data Science Handbook, 2023, pp 353-374 from Springer

Abstract: Abstract An autoencoder is a specific type of a neural network, which is mainly designed to encode the input into a compressed and meaningful representation and then decode it back such that the reconstructed input is similar as possible to the original one. This chapter surveys the different types of autoencoders that are mainly used today. It also describes various applications and use-cases of autoencoders.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-24628-9_16

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DOI: 10.1007/978-3-031-24628-9_16

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