An Introduction to Variational Autoencoders

被引:1470
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
收藏
页码:4 / 89
页数:86
相关论文
共 139 条
[1]  
[Anonymous], 2015, CoRR abs/1511.05644
[2]  
[Anonymous], P 33 INT C INT C MAC
[3]  
[Anonymous], 2017, INT C LEARN REPR
[4]  
[Anonymous], 2018, 32 AAAI C ART INT
[5]  
[Anonymous], 2017, AAAI C ART INT
[6]  
[Anonymous], BENELEARN 2017
[7]  
[Anonymous], 2017, ICLR
[8]  
[Anonymous], INT C LEARN REPR
[9]  
[Anonymous], 2017, INT C LEARNING REPRE
[10]  
[Anonymous], 2016, ARXIV160508803CSSTAT