An Introduction to Variational Autoencoders

被引：1487

作者：

Kingma, Diederik P. ^{[1
]}

Welling, Max ^{[2
,3
]}

机构：

[1] Google, Mountain View, CA 94043 USA

[2] Univ Amsterdam, Amsterdam, Netherlands

[3] Qualcomm, San Diego, CA USA

来源：

FOUNDATIONS AND TRENDS IN MACHINE LEARNING | 2019年 / 12卷 / 04期

关键词：

GRADIENT; LIKELIHOOD; ALGORITHMS; MODELS;

D O I：

10.1561/2200000056

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：4 / 89

页数：86

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