mlsanityData to 7 Oct 2026

Autoencoders

arXiv 2003.05991 ↗First posted 12 Mar 2020cs.LG cs.CV stat.MLcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Mar 2020.

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Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023Model of models -- Part 1cited by 0
  2. 2024Artificial Neural Networks for Photonic Applications: From Algorithms to Implementationcited by 0