On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields

DOI10.1007/s10444-024-10189-6MaRDI QIDQ6624464

Paolo Zunino, Daniel Fraulin, Nicola Rares Franco, Andrea Manzoni

Publication date: 25 October 2024

Published in: Advances in Computational Mathematics (Search for Journal in Brave)

zbMATH Keywords

random fieldsreduced order modelingdeep learningautoencodersparametrized PDEs

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Dependence of solutions to PDEs on initial and/or boundary data and/or on parameters of PDEs (35B30) Theoretical approximation in context of PDEs (35A35) Numerical analysis (65-XX)

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