2 papers
math.NA2026
Multi-type Sensor Placement for PDE-based Bayesian Inverse Problems
Steven Maio, Alen Alexanderian, Karina Koval +1
We address optimal placement of multi-type sensors for Bayesian inverse problems governed by partial differential equations (PDEs). The proposed framework allows for sensors with d…
math.OC2026
Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging
Tiangang Cui, Karina Koval, Roland Herzog +1
We propose a novel approach for sequential optimal experimental design (sOED) for Bayesian inverse problems involving expensive models with high-dimensional unknown parameters. Thi…