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math.NA2026

On Fourier Phase Retrieval from Differential Intensity Measurements with Applications to Wavefront Sensing

Simon Hubmer, Lukas Weissinger, Ronny Ramlau +1

In this paper, we consider Fourier phase retrieval from differential intensity measurements, i.e., the problem of determining the phase of a complex-valued function from a series o…

math.NA2026

Neural operators for solving nonlinear inverse problems

Otmar Scherzer, Thi Lan Nhi Vu, Jikai Yan

We consider solving a probably infinite dimensional operator equation, where the operator is not modeled by physical laws but is specified indirectly via training pairs of the inpu…

math.NA2026

Raster Scan Diffraction Tomography

Peter Elbau, Noemi Naujoks, Otmar Scherzer

Diffraction tomography is a widely used inverse scattering technique for quantitative imaging of weakly scattering media. In its conventional formulation, diffraction tomography as…

math.NA2025

Addendum on data driven regularization by projection

Martin Hanke, Otmar Scherzer

We study the stability of regularization by projection for solving linear inverse problems if the forward operator is given indirectly but specified via some input-output training…

math.NA2024

Vertex characterization via second-order topological derivatives

Peter Gangl, Bochra Mejri, Otmar Scherzer

This paper focuses on identifying vertex characteristics in 2D images using topological asymptotic analysis. Vertex characteristics include both the location and the type of the ve…

math.NA2024

Spectral Function Space Learning and Numerical Linear Algebra Networks for Solving Linear Inverse Problems

Andrea Aspri, Leon Frischauf, Otmar Scherzer

We consider solving a probably ill-conditioned linear operator equation, where the operator is not modeled by physical laws but is specified via training pairs (consisting of image…