Maximilian März

20 papers A* 1Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Sampling Rates for ℓ Found. Comput. Math. Maximilian März, Claire Boyer, Jonas Kahn, Pierre Weiss
2023	J	`jnl`	Solving Inverse Problems With Deep Neural Networks - Robustness Included? IEEE Trans. Pattern Anal. Mach. Intell. Martin Genzel, Jan MacDonald, Maximilian März
2022	J	`jnl`	Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images. CoRR Theophil Trippe, Martin Genzel, Jan MacDonald, Maximilian März
2022	A*	`conf`	Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning. ICML Martin Genzel, Ingo Gühring, Jan MacDonald, Maximilian März
2022	J	`jnl`	Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning. CoRR Martin Genzel, Ingo Gühring, Jan MacDonald, Maximilian März
2021	J	`jnl`	AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry. CoRR Martin Genzel, Jan MacDonald, Maximilian März
2021	J	`jnl`	Detecting failure modes in image reconstructions with interval neural network uncertainty. Int. J. Comput. Assist. Radiol. Surg. Luis Oala, Cosmas Heiß, Jan MacDonald, Maximilian März, Gitta Kutyniok, Wojciech Samek
2021	—	`conf`	Interval Neural Networks as Instability Detectors for Image Reconstructions. Bildverarbeitung für die Medizin Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek
2021	—	`—`	Solving underdetermined inverse problems: from advanced sparsity models to deep learning. Maximilian März
2020	J	`jnl`	Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery (iTWIST'20). CoRR Martin Genzel, Maximilian März, Robert Seidel
2020	J	`jnl`	Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery. CoRR Martin Genzel, Maximilian März, Robert Seidel
2020	J	`jnl`	Correcting the Side Effects of ADC Filtering in MR Image Reconstruction. J. Math. Imaging Vis. Carole Lazarus, Maximilian März, Pierre Weiss
2020	J	`jnl`	Interval Neural Networks as Instability Detectors for Image Reconstructions. CoRR Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek
2020	J	`jnl`	Interval Neural Networks: Uncertainty Scores. CoRR Luis Oala, Cosmas Heiss, Jan MacDonald, Maximilian März, Wojciech Samek, Gitta Kutyniok
2020	J	`jnl`	Sampling Rates for 𝓁 CoRR Maximilian März, Claire Boyer, Jonas Kahn, Pierre Weiss
2020	J	`jnl`	Solving Inverse Problems With Deep Neural Networks - Robustness Included? CoRR Martin Genzel, Jan MacDonald, Maximilian März
2018	J	`jnl`	Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. CoRR Tatiana A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan
2017	J	`jnl`	$\ell^1$-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed? CoRR Martin Genzel, Gitta Kutyniok, Maximilian März
2017	J	`jnl`	Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting. CoRR Jackie Ma, Maximilian März, Stephanie Funk, Jeanette Schulz-Menger, Gitta Kutyniok, Tobias Schaeffter, Christoph Kolbitsch
2016	—	`conf`	Combined Background Field Removal and Reconstruction for Quantitative Susceptibility Mapping. Bildverarbeitung für die Medizin Maximilian März, Lars Ruthotto