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Paper Abstract and Keywords
Presentation 2020-01-24 10:10
Optimal Transport based Autoencoder for class and style Disentanglement
Florian Tambon, Tetsuo Furukawa (Kyutech) NC2019-62
Abstract (in Japanese) (See Japanese page) 
(in English) The Sinkhorn autoencoder is a novel generative model using optimal transport to model the aggregated posterior from samples, hence discarding traditional reparametrization trick from classical Variational Autoencoder (VAE) and allowing better flexibility of metrics spaces and priors. Yet, one of the down side of all latent space modelling methods is the lack of interpretability and the potential entanglement problem. The aim of this work is to extend the Sinkhorn Autoencoder to better disentangle the latent space by focusing on the class/style separation approach while providing better interpretability and generative capability. Thus, our method would help further expand knowledge regarding optimal transport based generative model.
Keyword (in Japanese) (See Japanese page) 
(in English) Generative model / Optimal Transport / Disentanglement / Sinkhorn Loss / Autoencoder / Latent Space / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 382, NC2019-62, pp. 17-22, Jan. 2020.
Paper # NC2019-62 
Date of Issue 2020-01-16 (NC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NC2019-62

Conference Information
Committee NLP NC  
Conference Date 2020-01-23 - 2020-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Miyakojima Marine Terminal 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2020-01-NLP-NC 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimal Transport based Autoencoder for class and style Disentanglement 
Sub Title (in English)  
Keyword(1) Generative model  
Keyword(2) Optimal Transport  
Keyword(3) Disentanglement  
Keyword(4) Sinkhorn Loss  
Keyword(5) Autoencoder  
Keyword(6) Latent Space  
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1st Author's Name Florian Tambon  
1st Author's Affiliation Kyushu Institute of Technology (Kyutech)
2nd Author's Name Tetsuo Furukawa  
2nd Author's Affiliation Kyushu Institute of Technology (Kyutech)
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Speaker
Date Time 2020-01-24 10:10:00 
Presentation Time 20 
Registration for NC 
Paper # IEICE-NC2019-62 
Volume (vol) IEICE-119 
Number (no) no.382 
Page pp.17-22 
#Pages IEICE-6 
Date of Issue IEICE-NC-2020-01-16 


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