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  Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems

Kapadia, H., Feng, L., & Benner, P. (2024). Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems. Computer Methods in Applied Mechanics and Engineering, 419: 116657. doi:10.1016/j.cma.2023.116657.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-4DBC-A Version Permalink: https://hdl.handle.net/21.11116/0000-000F-37BF-D
Genre: Journal Article

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© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC license.
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 Creators:
Kapadia, Harshit1, Author           
Feng, Lihong1, Author           
Benner, Peter1, Author                 
Affiliations:
1Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738141              

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 Dates: 2023-06-0920232024
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: arXiv: 2306.06174
DOI: 10.1016/j.cma.2023.116657
Other: pubdata_escidoc:3514920
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Title: Computer Methods in Applied Mechanics and Engineering
Source Genre: Journal
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Pages: - Volume / Issue: 419 Sequence Number: 116657 Start / End Page: - Identifier: -