86 citations · 265 across the 18 of their papers we have counts for
4 papers · 2 filters
Bayesian view on the training of invertible residual networks for solving linear inverse problems
Clemens Arndt, Sören Dittmer, Nick Heilenkötter +3
Learning-based methods for inverse problems, adapting to the data's inherent structure, have become ubiquitous in the last decade. Besides empirical investigations of their often r…
Learning-based approaches for reconstructions with inexact operators in nanoCT applications
Tom Lütjen, Fabian Schönfeld, Alice Oberacker +4
Imaging problems such as the one in nanoCT require the solution of an inverse problem, where it is often taken for granted that the forward operator, i.e., the underlying physical…
Dynamic image reconstruction with motion priors in application to 3D magnetic particle imaging
Christina Brandt, Tobias Kluth, Tobias Knopp +1
Various imaging modalities allow for time-dependent image reconstructions from measurements where its acquisition also has a time-dependent nature. Magnetic particle imaging (MPI)…
Invertible residual networks in the context of regularization theory for linear inverse problems
Clemens Arndt, Alexander Denker, Sören Dittmer +5
Learned inverse problem solvers exhibit remarkable performance in applications like image reconstruction tasks. These data-driven reconstruction methods often follow a two-step sch…