Martin Genzel

Solving Inverse Problems With Deep Neural Networks – Robustness Included?

Martin Genzel, Jan Macdonald, Maximilian März · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2022 · 140 citations · Full text

Artificial Intelligence, Engineering, Machine Learning +17

ℓ1-Analysis minimization and generalized (co-)sparsity: When does recovery succeed?

Martin Genzel, Gitta Kutyniok, Maximilian März · Applied and Computational Harmonic Analysis · 2020 · 70 citations · Full text

Numerical Analysis, Sparse Representation, Engineering +5

Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning

Martin Genzel, Ingo Gühring, Jan Macdonald et al. · arXiv (Cornell University) · 2022 · 30 citations · Full text

Geometric Learning, Image Reconstruction, Engineering +19

of Sparse Proteomics Analysis â a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

Tim Conrad, Martin Genzel, Nada Cvetković et al. · Figshare · 2019 · 29 citations · Full text

Rietveld-based energy-dispersive residual stress evaluation: analysis of complex stress fields σ_<i>ij</i>(<i>z</i>)

Daniel Apel, Manuela Klaus, Martin Genzel et al. · Journal of Applied Crystallography · 2014 · 13 citations

Engineering, Mechanical Engineering, Residual Stress +19