4 papers
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
Martin Genzel, Jan Macdonald, Maximilian März
This report is dedicated to a short motivation and description of our contribution to the AAPM DL-Sparse-View CT Challenge (team name: "robust-and-stable"). The task is to recover…
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery (iTWIST'20)
Martin Genzel, Maximilian März, Robert Seidel
This paper investigates total variation minimization in one spatial dimension for the recovery of gradient-sparse signals from undersampled Gaussian measurements. Recently establis…
The Mismatch Principle: The Generalized Lasso Under Large Model Uncertainties
Martin Genzel, Gitta Kutyniok
We study the estimation capacity of the generalized Lasso, i.e., least squares minimization combined with a (convex) structural constraint. While Lasso-type estimators were origina…
Robust 1-Bit Compressed Sensing via Hinge Loss Minimization
Martin Genzel, Alexander Stollenwerk
This work theoretically studies the problem of estimating a structured high-dimensional signal from noisy -bit Gaussian measurements. Our recovery approac…