6 citations · 7 across the 4 of their papers we have counts for
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Data-proximal null-space networks for inverse problems
Simon Göppel, Jürgen Frikel, Markus Haltmeier
Inverse problems are inherently ill-posed and therefore require regularization techniques to achieve a stable solution. While traditional variational methods have well-established…
Translation invariant diagonal frame decomposition for the Radon transform
Simon Göppel, Markus Haltmeier, Jürgen Frikel
In this article, we address the challenge of solving the ill-posed reconstruction problem in computed tomography using a translation invariant diagonal frame decomposition (TI-DFD)…
Translation invariant diagonal frame decomposition of inverse problems and their regularization
Simon Göppel, Jürgen Frikel, Markus Haltmeier
Solving inverse problems is central to a variety of important applications, such as biomedical image reconstruction and non-destructive testing. These problems are characterized by…