Differential equation constrained optimization problems with constituents that are only accessible through data-driven techniques are studied.
Aug 25, 2020 · Differential equation constrained optimization problems with constituents that are only accessible through data-driven techniques are studied.
Abstract. Inspired by applications in optimal control of semilinear elliptic partial differential equa- tions and physics-integrated imaging, differential ...
Oct 22, 2024 · A particular focus is on the analysis and on numerical methods for problems with machine-learned components. For a rather general context, an ...
A particular focus is on the analysis and on numerical methods for problems with machine-learned components. For a rather general context, an error analysis is ...
A numerical algorithm for solving a class of optimal control problems for learning-informed semilinear partial differential equations with constituents that ...
May 10, 2021 · In many PDE models, regularity of the resp. solution helps the weak-weak sequential closedness condition of the control-to-state map to be ...
PlumX Metrics provide insights into the ways people interact with individual pieces ofresearch output (articles, conference proceedings, book chapters, and many ...
May 10, 2021 · ... of Berlin) on "Optimization with Learning-Informed Differential Equation Constraints and Its Applications". The slides of the talk can be seen ...
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Aug 28, 2021 · Optimization with Learning-Informed Partial Differential Equation Constraints --- Guozhi Dong. 39 views · 3 years ago ...more. Try YouTube ...