21 citations · 64 across the 14 of their papers we have counts for
15 papers
Polytope Division Method: A Scalable Sampling Method for Problems with High-dimensional Parameters
Evie Nielen, Oliver Tse, Karen Veroy
Configuration Optimization Problems (COPs), which involve minimizing a loss function over a set of discrete points , are common in areas like Model Order Re…
Reduced-order modeling for second-order computational homogenization with applications to geometrically parameterized elastomeric metamaterials
T. Guo, V. G. Kouznetsova, M. G. D. Geers +2
The structural properties of mechanical metamaterials are typically studied with two-scale methods based on computational homogenization. Because such materials have a complex micr…
An adaptive hierarchical ensemble Kalman filter with reduced basis models
Francesco A. B. Silva, Cecilia Pagliantini, Karen Veroy
The use of model order reduction techniques in combination with ensemble-based methods for estimating the state of systems described by nonlinear partial differential equations has…
A reduced order model for geometrically parameterized two-scale simulations of elasto-plastic microstructures under large deformations
Theron Guo, Ondřej Rokoš, Karen Veroy
In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an eff…
A Greedy Sensor Selection Algorithm for Hyperparameterized Linear Bayesian Inverse Problems
Nicole Aretz, Peng Chen, Denise Degen +1
We consider optimal sensor placement for a family of linear Bayesian inverse problems characterized by a deterministic hyper-parameter. The hyper-parameter describes distinct confi…
Choosing observation operators to mitigate model error in Bayesian inverse problems
Nada Cvetković, Han Cheng Lie, Harshit Bansal +1
In statistical inference, a discrepancy between the parameter-to-observable map that generates the data and the parameter-to-observable map that is used for inference can lead to m…
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…
Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: Extension to geometrical parameterizations
Theron Guo, Francesco A. B. Silva, Ondřej Rokoš +1
Understanding structure-property relations is essential to optimally design materials for specific applications. Two-scale simulations are often employed to analyze the effect of t…
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
Philipp Diercks, Karen Veroy, Annika Robens-Radermacher +1
In this paper, a methodology for fine scale modeling of large scale structures is proposed, which combines the variational multiscale method, domain decomposition and model order r…
Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method
Theron Guo, Ondřej Rokoš, Karen Veroy
In order to optimally design materials, it is crucial to understand the structure-property relations in the material by analyzing the effect of microstructure parameters on the mac…
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,…
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…
A Duality Approach to Error Estimation for Variational Inequalities
Zhenying Zhang, Eduard Bader, Karen Veroy
Motivated by problems in contact mechanics, we propose a duality approach for computing approximations and associated a posteriori error bounds to solutions of variational inequali…
Reduced Basis A Posteriori Error Bounds for Symmetric Parametrized Saddle Point Problems
Anna-Lena Gerner, Karen Veroy
This paper directly builds upon previous work where we introduced new reduced basis a posteriori error bounds for parametrized saddle point problems based on Brezzi's theory. We he…
Reduced Basis A Posteriori Error Bounds for the Instationary Stokes Equations
Anna-Lena Gerner, Arnold Reusken, Karen Veroy
We present reduced basis approximations and rigorous a posteriori error bounds for the instationary Stokes equations. We shall discuss both a method based on the standard formulati…