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Autoencoders - 2020

Research Area:  Machine Learning

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.

Author(s) Name:  Dor Bank, Noam Koenigstein, Raja Giryes

Journal name:  arXiv.org/cs

Conferrence name:  

Publisher name:  arXiv.org

DOI:  arXiv:2003.05991

Volume Information:  arXiv:2003.05991