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Paper Abstract and Keywords
Presentation 2026-01-26 16:15
[Invited Talk] Recent Advances in Physics-Informed Neural Networks
Shota Deguchi (Univ. of Tsukuba) CQ2025-85
Abstract (in Japanese) (See Japanese page) 
(in English) With the rapid advancements in machine learning approaches, there has been an increasing demand for interpretability and reliability of such models. Consequently, there has been a surge in the development of models that incorporate prior knowledge, replacing traditional models that require large amounts of data. These approaches have been demonstrated to enhance performance, as well as data efficiency and reliability. Physics-Informed Neural Networks (PINNs), in particular, utilize governing equations as a prior, allowing for flexible handling of both forward and inverse problems. This study presents the fundamentals of PINNs and recent progress in this field.
Keyword (in Japanese) (See Japanese page) 
(in English) Scientific Machine Learning / Physics-Informed Machine Learning / Physics-Informed Neural Network / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 335, CQ2025-85, pp. 57-58, Jan. 2026.
Paper # CQ2025-85 
Date of Issue 2026-01-19 (CQ) 
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 CQ2025-85

Conference Information
Committee CQ CBE  
Conference Date 2026-01-26 - 2026-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) The Beppu Chamber of Commerce and Industry 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network Science, Computational Social Science, Human Computer Interaction, Data Analysis, User Behaviour, Media Quality, etc. 
Paper Information
Registration To CQ 
Conference Code 2026-01-CQ-CBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Recent Advances in Physics-Informed Neural Networks 
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Keyword(1) Scientific Machine Learning  
Keyword(2) Physics-Informed Machine Learning  
Keyword(3) Physics-Informed Neural Network  
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1st Author's Name Shota Deguchi  
1st Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
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Speaker Author-1 
Date Time 2026-01-26 16:15:00 
Presentation Time 35 minutes 
Registration for CQ 
Paper # CQ2025-85 
Volume (vol) vol.125 
Number (no) no.335 
Page pp.57-58 
#Pages 2 
Date of Issue 2026-01-19 (CQ) 

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