Dirichlet Variational Autoencoder

•This paper is a study on Dirichlet prior in variational autoencoder.•Our model outperforms baseline variational autoencoders in the perspective of loglikelihood.•Our model produces more meaningful and interpretable latent representation with no component collapsing compared to baseline variational...

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Bibliographic Details

Published in:	Pattern recognition Vol. 107; p. 107514
Main Authors:	Joo, Weonyoung, Lee, Wonsung, Park, Sungrae, Moon, Il-Chul
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2020
Subjects:	Component collapse Deep generative model Multi-modal latent representation Representation learning Variational autoencoder Representation learning Variational autoencoder Deep generative model Component collapse Multi-modal latent representation
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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