Jan MacDonald

According to our database, Jan MacDonald authored at least 15 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Solving Inverse Problems With Deep Neural Networks - Robustness Included?

Martin Genzel, Jan MacDonald, Maximilian März

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

2022

The reliability of deep learning for signal and image processing: Interpretability, robustness, and accuracy.

Jan MacDonald

PhD thesis, 2022

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

Theophil Trippe, Martin Genzel, Jan MacDonald, Maximilian März

CoRR, 2022

Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings.

Jan MacDonald, Mathieu Besançon, Sebastian Pokutta

Proceedings of the International Conference on Machine Learning, 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

A Complete Characterisation of ReLU-Invariant Distributions.

Jan MacDonald, Stephan Wäldchen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

The Computational Complexity of Understanding Binary Classifier Decisions.

Stephan Wäldchen, Jan MacDonald, Sascha Hauch, Gitta Kutyniok

J. Artif. Intell. Res., 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

Interval Neural Networks: Uncertainty Scores.

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

CoRR, 2020

2019

A Rate-Distortion Framework for Explaining Neural Network Decisions.

Jan MacDonald, Stephan Wäldchen, Sascha Hauch, Gitta Kutyniok

CoRR, 2019

The Computational Complexity of Understanding Network Decisions.

Stephan Wäldchen, Jan MacDonald, Sascha Hauch, Gitta Kutyniok

CoRR, 2019

The Oracle of DLphi.

Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan MacDonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber

CoRR, 2019

2018

Improved Susceptibility Artifact Correction of Echo-Planar MRI using the Alternating Direction Method of Multipliers.

Jan MacDonald, Lars Ruthotto

J. Math. Imaging Vis., 2018