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20132026
most citedScalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

171 citations · 211 across the 10 of their papers we have counts for

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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,…