Maximilian März

According to our database, Maximilian März authored at least 16 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Sampling Rates for ℓ ¹-Synthesis.

Maximilian März, Claire Boyer, Jonas Kahn, Pierre Weiss

Found. Comput. Math., December, 2023

Solving Inverse Problems With Deep Neural Networks - Robustness Included?

Martin Genzel, Jan MacDonald, Maximilian März

IEEE Trans. Pattern Anal. Mach. Intell., 2023

2022

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

Theophil Trippe, Martin Genzel, Jan MacDonald, Maximilian März

CoRR, 2022

Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning.

Martin Genzel, Ingo Gühring, Jan MacDonald, Maximilian März

Proceedings of the International Conference on Machine Learning, 2022

2021

Solving underdetermined inverse problems: from advanced sparsity models to deep learning.

Maximilian März

PhD thesis, 2021

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

Martin Genzel, Jan MacDonald, Maximilian März

CoRR, 2021

Detecting failure modes in image reconstructions with interval neural network uncertainty.

Luis Oala, Cosmas Heiß, Jan MacDonald, Maximilian März, Gitta Kutyniok, Wojciech Samek

Int. J. Comput. Assist. Radiol. Surg., 2021

Interval Neural Networks as Instability Detectors for Image Reconstructions.

Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

Correcting the Side Effects of ADC Filtering in MR Image Reconstruction.

Carole Lazarus, Maximilian März, Pierre Weiss

J. Math. Imaging Vis., 2020

Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery (iTWIST'20).

Martin Genzel, Maximilian März, Robert Seidel

CoRR, 2020

Interval Neural Networks: Uncertainty Scores.

Luis Oala, Cosmas Heiss, Jan MacDonald, Maximilian März, Wojciech Samek, Gitta Kutyniok

CoRR, 2020

Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery.

Martin Genzel, Maximilian März, Robert Seidel

CoRR, 2020

2018

Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography.

Tatiana A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan

CoRR, 2018

2017

$\ell^1$-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed?

Martin Genzel, Gitta Kutyniok, Maximilian März

CoRR, 2017

Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting.

Jackie Ma, Maximilian März, Stephanie Funk, Jeanette Schulz-Menger, Gitta Kutyniok, Tobias Schaeffter, Christoph Kolbitsch

CoRR, 2017

2016

Combined Background Field Removal and Reconstruction for Quantitative Susceptibility Mapping.

Maximilian März, Lars Ruthotto

Proceedings of the Bildverarbeitung für die Medizin 2016 - Algorithmen - Systeme, 2016