150 citations · 423 across the 23 of their papers we have counts for
5 papers · 1 filter
Solving Inverse Problems With Deep Neural Networks -- Robustness Included?
Martin Genzel, Jan Macdonald, Maximilian März
In the past five years, deep learning methods have become state-of-the-art in solving various inverse problems. Before such approaches can find application in safety-critical field…
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…
A Unified Approach to Uniform Signal Recovery From Non-Linear Observations
Martin Genzel, Alexander Stollenwerk
Recent advances in quantized compressed sensing and high-dimensional estimation have shown that signal recovery is even feasible under strong non-linear distortions in the observat…
Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data
Martin Genzel, Christian Kipp
This work performs a non-asymptotic analysis of the generalized Lasso under the assumption of sub-exponential data. Our main results continue recent research on the benchmark case…
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery
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…