Distributed learning machines for solving forward and inverse problems in partial differential equations

We conceptualize Distributed Learning Machines (DLMs) – a novel machine learning approach that integrates existing machine learning algorithms with traditional mesh-based numerical methods for solving forward and inverse problems in nonlinear partial differential equations (PDEs). In conventional nu...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 420; pp. 299 - 316
Main Authors:	Dwivedi, Vikas, Parashar, Nishant, Srinivasan, Balaji
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 08.01.2021
Subjects:	Burgers’ equation Distributed physics informed neural networks Inverse problems Navier–Stokes equation Transfer learning Burgers’ equation Inverse problems Navier–Stokes equation Transfer learning Distributed physics informed neural networks
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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