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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.NA2024
Non-intrusive optimal experimental design for large-scale nonlinear Bayesian inverse problems using a Bayesian approximation error approach
Karina Koval, Ruanui Nicholson
We consider optimal experimental design (OED) for nonlinear inverse problems within the Bayesian framework. Optimizing the data acquisition process for large-scale nonlinear Bayesi…