139 citations · 555 across the 26 of their papers we have counts for
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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…
Regularized Orthogonal Nonnegative Matrix Factorization and -means Clustering
Pascal Fernsel, Peter Maass
In this work, we focus on connections between -means clustering approaches and Orthogonal Nonnegative Matrix Factorization (ONMF) methods. We present a novel framework to extrac…
Joint super-resolution image reconstruction and parameter identification in imaging operator: Analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging
Tobias Kluth, Christine Bathke, Ming Jiang +1
One important property of imaging modalities and related applications is the resolution of image reconstructions which relies on various factors such as instrumentation or data pro…
Error analysis for filtered back projection reconstructions in Besov spaces
Matthias Beckmann, Peter Maass, Judith Nickel
Filtered back projection (FBP) methods are the most widely used reconstruction algorithms in computerized tomography (CT). The ill-posedness of this inverse problem allows only an…