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math.OC2020
Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: good to know what you don't know
Alen Alexanderian, Noemi Petra, Georg Stadler +1
We consider optimal design of infinite-dimensional Bayesian linear inverse problems governed by partial differential equations that contain secondary reducible model uncertainties,…
math.OC2019
Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs
Karina Koval, Alen Alexanderian, Georg Stadler
We present a method for computing A-optimal sensor placements for infinite-dimensional Bayesian linear inverse problems governed by PDEs with irreducible model uncertainties. Here,…