Optimization with learning-informed differential equation constraints and its applications

DOI10.1051/cocv/2021100zbMath1481.49028arXiv2008.10893OpenAlexW3214160858WikidataQ114011518 ScholiaQ114011518MaRDI QIDQ5024338

Guozhi Dong, Kostas Papafitsoros, Michael Hintermüller

Publication date: 31 January 2022

Published in: ESAIM: Control, Optimisation and Calculus of Variations (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.10893

zbMATH Keywords

optimal controlartificial neural networksemilinear PDEsquantitative MRIintegrated physics-based imaginglearning-informed modelsemi-smooth Newton SQP algorithm

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Numerical solutions to equations with nonlinear operators (65J15) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Semilinear elliptic equations (35J61)

Related Items

Learning-informed parameter identification in nonlinear time-dependent PDEs, On the identification and optimization of nonsmooth superposition operators in semilinear elliptic PDEs

Uses Software

• PATH Solver
• BrainWeb
• PDE-Net
• DGM

Cites Work

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