An Introduction to Variational Autoencoders

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 28 Nov 2019Embargo end date: 01 Jun 2019 English Publisher:EmeraldJournal:Foundations and Trends® in Machine Learning, volume 12, pages 307-392 (issn: 1935-8237, eissn: 1935-8245,

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Authors: Diederik P. Kingma; Max Welling;

doi: 10.1561/2200000056 , 10.48550/arxiv.1906.02691

arXiv: 1906.02691

An Introduction to Variational Autoencoders

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Abstract

Variational autoencoders provide a principled framework for learning deep latent-variable models and corresponding inference models. In this work, we provide an introduction to variational autoencoders and some important extensions.

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Keywords

FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Machine Learning (stat.ML), Machine Learning (cs.LG)

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