activity
20152024
most citedA Fast Isogeometric BEM for the Three Dimensional Laplace- and Helmholtz Problems

61 citations · 89 across the 20 of their papers we have counts for

collaborators

32 papers

math.OC2024

Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization

Marc Dambrine, Caroline Geiersbach, Helmut Harbrecht

The present article is dedicated to proving convergence of the stochastic gradient method in case of random shape optimization problems. To that end, we consider Bernoulli's exteri…

math.AP2023

The Gevrey class implicit mapping theorem with application to UQ of semilinear elliptic PDEs

Helmut Harbrecht, Marc Schmidlin, Christoph Schwab

This article is concerned with a regularity analysis of parametric operator equations with a perspective on uncertainty quantification. We study the regularity of mappings between…

math.NA2023

Solving acoustic scattering problems by the isogeometric boundary element method

Jürgen Dölz, Helmut Harbrecht, Michael Multerer

We solve acoustic scattering problems by means of the isogeometric boundary integral equation method. In order to avoid spurious modes, we apply the combined field integral equatio…

stat.ML2023

Samplet basis pursuit: Multiresolution scattered data approximation with sparsity constraints

Davide Baroli, Helmut Harbrecht, Michael Multerer

We consider scattered data approximation in samplet coordinates with -regularization. The application of an -regularization term enforces sparsity of the coefficien…

math.NA2022

Multiresolution kernel matrix algebra

H. Harbrecht, M. Multerer, O. Schenk +1

We propose a sparse algebra for samplet compressed kernel matrices, to enable efficient scattered data analysis. We show the compression of kernel matrices by means of samplets pro…

math.NA2022

Uncertainty quantification for random domains using periodic random variables

Harri Hakula, Helmut Harbrecht, Vesa Kaarnioja +2

We consider uncertainty quantification for the Poisson problem subject to domain uncertainty. For the stochastic parameterization of the random domain, we use the model recently in…