Project
AA-Tech-3
Low-Rank Approximation in Bayesian Optimal Experimental Design
Project Heads
Robert Gruhlke
Project Members
Robert Gruhlke
Project Duration
01.03.2026 − 28.02.2027
Located at
FU Berlin
Description
Functional low-rank approximations enable e!cient Bayesian optimal experimental design. This project integrates regression in low-rank manifolds via optimal sampling with gradient flow-based Bayesian inversion for parametric PDE problems with application to hyperspectral imaging and micro-weather control.
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