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Paper Abstract and Keywords
Presentation 2025-10-03 10:50
Hierarchical and Geometric Analysis of Features in Generative and Identificative Representation Learning
Kenya Jin'no (Tokyo City Univ.) CAS2025-32 NLP2025-49
Abstract (in Japanese) (See Japanese page) 
(in English) This article aims to elucidate how neural networks internally represent and transform data from the perspective of "manifold deformation." By contrasting "classifiers," which are discriminative representation learners, with "autoencoders," which are generative representation learners, we seek to reveal how the internal representations of neural networks with different learning objectives differ, and to clarify the underlying differences in their internal mechanisms.
Keyword (in Japanese) (See Japanese page) 
(in English) simplex ETF / neural collapse / classifier / autoencoder / manifold structure / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 190, NLP2025-49, pp. 72-77, Oct. 2025.
Paper # NLP2025-49 
Date of Issue 2025-09-25 (CAS, NLP) 
ISSN 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 CAS2025-32 NLP2025-49

Conference Information
Committee CAS NLP  
Conference Date 2025-10-02 - 2025-10-03 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Nonlinear Problems, Circuits and Systems, etc. 
Paper Information
Registration To NLP 
Conference Code 2025-10-CAS-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Hierarchical and Geometric Analysis of Features in Generative and Identificative Representation Learning 
Sub Title (in English)  
Keyword(1) simplex ETF  
Keyword(2) neural collapse  
Keyword(3) classifier  
Keyword(4) autoencoder  
Keyword(5) manifold structure  
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1st Author's Name Kenya Jin'no  
1st Author's Affiliation Tokyo City University (Tokyo City Univ.)
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Speaker Author-1 
Date Time 2025-10-03 10:50:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # CAS2025-32, NLP2025-49 
Volume (vol) vol.125 
Number (no) no.189(CAS), no.190(NLP) 
Page pp.72-77 
#Pages 6 
Date of Issue 2025-09-25 (CAS, NLP) 

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