2 papers
math.NA2020
A sequential sensor selection strategy for hyper-parameterized linear Bayesian inverse problems
Nicole Aretz-Nellesen, Peng Chen, Martin A. Grepl +1
We consider optimal sensor placement for hyper-parameterized linear Bayesian inverse problems, where the hyper-parameter characterizes nonlinear flexibilities in the forward model,…
math.OC2018
Reduced basis approximation and a~posteriori error bounds for 4D-Var data assimilation
Mark Kärcher, Sébastien Boyaval, Martin A. Grepl +1
We propose a certified reduced basis approach for the strong- and weak-constraint four-dimensional variational (4D-Var) data assimilation problem for a parametrized PDE model. Whil…