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Martin Genzel

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Self-Distilled Representation Learning for Time Series

Nov 19, 2023
Felix Pieper, Konstantin Ditschuneit, Martin Genzel, Alexandra Lindt, Johannes Otterbach

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Memorization with neural nets: going beyond the worst case

Oct 12, 2023
Sjoerd Dirksen, Patrick Finke, Martin Genzel

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Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models

May 19, 2023
Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel

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Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images

Nov 18, 2022
Theophil Trippe, Martin Genzel, Jan Macdonald, Maximilian März

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Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning

Jun 14, 2022
Martin Genzel, Ingo Gühring, Jan Macdonald, Maximilian März

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Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Feb 07, 2022
Jonathan Sauder, Martin Genzel, Peter Jung

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The Separation Capacity of Random Neural Networks

Jul 31, 2021
Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk

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AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry

Jun 01, 2021
Martin Genzel, Jan Macdonald, Maximilian März

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Solving Inverse Problems With Deep Neural Networks -- Robustness Included?

Nov 09, 2020
Martin Genzel, Jan Macdonald, Maximilian März

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Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data

May 18, 2020
Martin Genzel, Christian Kipp

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