1 citations · 1 across the 6 of their papers we have counts for
7 papers
JCGM 101-compliant uncertainty evaluation using virtual experiments
Finn Hughes, Manuel Marschall, Gerd Wübbeler +3
Virtual experiments (VEs), a modern tool in metrology, can be used to help perform an uncertainty evaluation for the measurand. Current guidelines in metrology do not cover the man…
Bayesian uncertainty evaluation applied to the tilted-wave interferometer
Manuel Marschall, Ines Fortmeier, Manuel Stavridis +2
The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surf…
Assessment of sub-sampling schemes for compressive nano-FTIR imaging
Selma Metzner, Bernd Kästner, Manuel Marschall +6
Nano-FTIR imaging is a powerful scanning-based technique at nanometer spatial resolution which combines Fourier transform infrared spectroscopy (FTIR) and scattering-type scanning…
Generative models and Bayesian inversion using Laplace approximation
Manuel Marschall, Gerd Wübbeler, Franko Schmähling +1
The Bayesian approach to solving inverse problems relies on the choice of a prior. This critical ingredient allows the formulation of expert knowledge or physical constraints in a…
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion
Martin Eigel, Robert Gruhlke, Manuel Marschall
Transport maps have become a popular mechanic to express complicated probability densities using sample propagation through an optimized push-forward. Beside their broad applicabil…
An adaptive stochastic Galerkin tensor train discretization for randomly perturbed domains
Martin Eigel, Manuel Marschall, Michael Multerer
A linear PDE problem for randomly perturbed domains is considered in an adaptive Galerkin framework. The perturbation of the domain's boundary is described by a vector valued rando…
Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations
Martin Eigel, Manuel Marschall, Max Pfeffer +1
Stochastic Galerkin methods for non-affine coefficient representations are known to cause major difficulties from theoretical and numerical points of view. In this work, an adaptiv…