Dynamical Variational Autoencoders

A Comprehensive Review

by Laurent Girin, Simon Leglaive, Xavier Alameda-Pineda, Julien Diard, Thomas Hueber e Xiaoyu Bie
language: english
Publisher: NOW PUBLISHERS INC, December of 2021 ‧
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Variational autoencoders are powerful deep generative models widely used to represent high-dimensional complex data through a low-dimensional latent space learned in an unsupervised manner. In this volume, the authors introduce and discuss a general class of models, called dynamical variational autoencoders.

Dynamical Variational Autoencoders

A Comprehensive Review

by Laurent Girin, Simon Leglaive, Xavier Alameda-Pineda, Julien Diard, Thomas Hueber e Xiaoyu Bie

Property Description
ISBN: 9781680839128
Publisher: NOW PUBLISHERS INC
Release Date: December of 2021
Language: English
Dimensions: 156 x 234 x 20 mm
Cover: Softcover
Pages: 198
Format: Book
Collection: St. James'S Studies In World Affairs
Categories: Books in English > Computing > Other Applications
Books in English > Others
EAN: 9781680839128

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