Non‐intrusive reduced‐order modeling using convolutional autoencoders

DOI10.1002/nme.7072arXiv2204.08280OpenAlexW4224254947MaRDI QIDQ6092270

Kevin J. Maki, Unnamed Author, Krzysztof J. Fidkowski

Publication date: 23 November 2023

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2204.08280

zbMATH Keywords

proper orthogonal decompositionmodel reductionmachine learningdeep learningautoencodersnon-intrusive

Mathematics Subject Classification ID

Numerical linear algebra (65Fxx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Incompressible viscous fluids (76Dxx)

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