One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty-Reference-Cited by-同舟云学术

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One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty

Published:2024-06-12 Issue:2 Volume:12 Page:614-645
ISSN:2166-2525
Container-title:SIAM/ASA Journal on Uncertainty Quantification
language:en
Short-container-title:SIAM/ASA J. Uncertainty Quantification

Author:

Guth Philipp A.¹,Schillings Claudia²,Weissmann Simon³

Affiliation:

1. Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences, Altenbergerstraße 69, 4040 Linz, Austria.

2. Fachbereich Mathematik und Informatik, Freie Universität Berlin, Arnimallee 6, 14195, Berlin, Germany.

3. Institute of Mathematics, University of Mannheim, 68138, Mannheim, Germany.

Funder

Deutsche Forschungsgemeinschaft

Baden-Württemberg Stiftung

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference48 articles.

1. Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations

2. Multilevel Monte Carlo Analysis for Optimal Control of Elliptic PDEs with Random Coefficients

3. A certified model reduction approach for robust parameter optimization with PDE constraints

4. Parametric PDEs: sparse or low-rank approximations?

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