Synonyms
Definition
An autoencoder is a deep neural architecture comprising two parts, namely, (1) an encoder network that maps each input data point to a point in a different (latent) space and (2) a decoder network that maps the points in the latent space back to the data space. The two components are trained jointly in an unsupervised way, so that their composition approximately preserves points from a given training dataset.
Background
Autoencoders are a very popular deep architecture for unsupervised learning going back to at least 1980s [1, 2]. Similar to other unsupervised learning methods such as principal component analysis [3], the objective of autoencoder learning is to find some latent representation of the points in a training dataset that...
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References
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Lempitsky, V. (2020). Autoencoder. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_862-1
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DOI: https://doi.org/10.1007/978-3-030-03243-2_862-1
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