3 citations · 5 across the 4 of their papers we have counts for
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Error Estimates for Data-driven Weakly Convex Frame-based Image Regularization
Andrea Ebner, Matthias Schwab, Markus Haltmeier
Inverse problems are fundamental in fields like medical imaging, geophysics, and computerized tomography, aiming to recover unknown quantities from observed data. However, these pr…
Convergence of non-linear diagonal frame filtering for regularizing inverse problems
Andrea Ebner, Markus Haltmeier
Inverse problems are key issues in several scientific areas, including signal processing and medical imaging. Since inverse problems typically suffer from instability with respect…
Plug-and-Play image reconstruction is a convergent regularization method
Andrea Ebner, Markus Haltmeier
Non-uniqueness and instability are characteristic features of image reconstruction processes. As a result, it is necessary to develop regularization methods that can be used to com…
Regularization of Inverse Problems by Filtered Diagonal Frame Decomposition
Andrea Ebner, Jürgen Frikel, Dirk Lorenz +2
The characteristic feature of inverse problems is their instability with respect to data perturbations. In order to stabilize the inversion process, regularization methods have to…