Tensor decomposition-based neural operator with dynamic mode decomposition for parameterized time-dependent problems

Deep operator networks (DeepONets), as a powerful tool to approximate nonlinear mappings between different function spaces, have gained significant attention recently for applications in modeling parameterized partial differential equations. However, limited by the poor extrapolation ability of pure...

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Bibliographic Details

Published in:	Journal of computational physics Vol. 533; p. 113996
Main Authors:	Chen, Yuanhong, Lin, Yifan, Sun, Xiang, Yuan, Chunxin, Gao, Zhen
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 15.07.2025
Subjects:	DeepONet Dynamic mode decomposition Parameterized time-dependent PDEs Tensor train decomposition DeepONet Parameterized time-dependent PDEs Dynamic mode decomposition Tensor train decomposition
ISSN:	0021-9991
Online Access:	Get full text
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