1 citations · 1 across the 3 of their papers we have counts for
5 papers
A Reduced Basis Ensemble Kalman Method
Francesco A. B. Silva, Cecilia Pagliantini, Martin Grepl +1
In the process of reproducing the state dynamics of parameter dependent distributed systems, data from physical measurements can be incorporated into the mathematical model to redu…
Reduced Order Model Predictive Control for Parametrized Parabolic Partial Differential Equations
Saskia Dietze, Martin A. Grepl
Model Predictive Control (MPC) is a well-established approach to solve infinite horizon optimal control problems. Since optimization over an infinite time horizon is generally infe…
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,…
3D-VAR for Parametrized Partial Differential Equations: A Certified Reduced Basis Approach
Nicole Aretz-Nellesen, Martin A. Grepl, Karen Veroy
In this paper, we propose a reduced order approach for 3D variational data assimilation governed by parametrized partial differential equations. In contrast to the classical 3D-VAR…
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…