54 citations · 71 across the 10 of their papers we have counts for
4 papers · 1 filter
Bayesian inversion for electromyography using low-rank tensor formats
Anna Rörich, Tim A. Werthmann, Dominik Göddeke +1
The reconstruction of the structure of biological tissue using electromyographic data is a non-invasive imaging method with diverse medical applications. Mathematically, this proce…
A parameter-dependent smoother for the multigrid method
Lars Grasedyck, Maren Klever, Christian Löbbert +1
The solution of parameter-dependent linear systems, by classical methods, leads to an arithmetic effort that grows exponentially in the number of parameters. This renders the multi…
Low-rank tensor methods for Markov chains with applications to tumor progression models
Peter Georg, Lars Grasedyck, Maren Klever +3
Continuous-time Markov chains describing interacting processes exhibit a state space that grows exponentially in the number of processes. This state-space explosion renders the com…
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format
Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck +1
Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up lar…