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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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Showing 2014Show all

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math.OC2014

A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems

Alen Alexanderian, Noemi Petra, Georg Stadler +1

We address the problem of optimal experimental design (OED) for Bayesian nonlinear inverse problems governed by PDEs. The goal is to find a placement of sensors, at which experimen…

math.OC2014★ 171 cited

Scalable 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

Tobin Isaac, Noemi Petra, Georg Stadler +1

The majority of research on efficient and scalable algorithms in computational science and engineering has focused on the forward problem: given parameter inputs, solve the governi…