Learning a reduced basis of dynamical systems using an autoencoder

Machine learning models have emerged as powerful tools in physics and engineering. In this work, we use an autoencoder with latent space penalization to discover approximate finite-dimensional manifolds of two canonical partial differential equations. We test this method on the Kuramoto-Sivashinsky...

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Bibliographic Details

Published in:	Physical review. E Vol. 104; no. 3-1; p. 034202
Main Authors:	Sondak, David, Protopapas, Pavlos
Format:	Journal Article
Language:	English
Published:	01.09.2021
ISSN:	2470-0053, 2470-0053
Online Access:	Get more information
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