Jan Macdonald

Generating author description...

All published works

Action	Title	Year	Authors
+ PDF Chat	Let's enhance: A deep learning approach to extreme deblurring of text images	2023	Theophil Trippe Martin Genzel Jan Macdonald Maximilian März
+ PDF Chat	Solving Inverse Problems With Deep Neural Networks – Robustness Included?	2022	Martin Genzel Jan Macdonald Maximilian März
+	Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning	2022	Martin Genzel Ingo Gühring Jan Macdonald Maximilian März
+	Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images	2022	Theophil Trippe Martin Genzel Jan Macdonald Maximilian März
+ PDF Chat	A Complete Characterisation of ReLU-Invariant Distributions	2021	Jan Macdonald Stephan Wäldchen
+	Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings.	2021	Jan Macdonald Mathieu Besançon Sebastian Pokutta
+	AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry.	2021	Martin Genzel Jan Macdonald Maximilian März
+ PDF Chat	Interval Neural Networks as Instability Detectors for Image Reconstructions	2021	Jan Macdonald Maximilian März Luis Oala Wojciech Samek
+	Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings	2021	Jan Macdonald Mathieu Besançon Sebastian Pokutta
+	AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry	2021	Martin Genzel Jan Macdonald Maximilian März
+	Interval Neural Networks: Uncertainty Scores	2020	Luis Oala Cosmas Heiß Jan Macdonald Maximilian März Wojciech Samek Gitta Kutyniok
+	Solving Inverse Problems With Deep Neural Networks -- Robustness Included?	2020	Martin Genzel Jan Macdonald Maximilian März
+	Interval Neural Networks as Instability Detectors for Image Reconstructions	2020	Jan Macdonald Maximilian März Luis Oala Wojciech Samek
+	A Rate-Distortion Framework for Explaining Neural Network Decisions.	2019	Jan Macdonald Stephan Wäldchen Sascha Hauch Gitta Kutyniok
+	The Computational Complexity of Understanding Network Decisions.	2019	Stephan Wäldchen Jan Macdonald Sascha Hauch Gitta Kutyniok
+	The Oracle of DLphi	2019	Dominik Alfke Weston Baines Jan Blechschmidt Mauricio J. del Razo Sarmina Amnon Drory Dennis Elbrächter Nando Farchmin Matteo Gambara Silke Glas Philipp Grohs
+	A Rate-Distortion Framework for Explaining Neural Network Decisions	2019	Jan Macdonald Stephan Wäldchen Sascha Hauch Gitta Kutyniok
+	The Computational Complexity of Understanding Network Decisions	2019	Stephan Wäldchen Jan Macdonald Sascha Hauch Gitta Kutyniok
+	The Oracle of DLphi	2019	Dominik Alfke Weston Baines Jan Blechschmidt Mauricio J. del Razo Sarmina Amnon Drory Dennis Elbrächter Nando Farchmin Matteo Gambara Silke Glas Philipp Grohs
+	Efficient Numerical Optimization For Susceptibility Artifact Correction Of EPI-MRI	2016	Jan Macdonald Lars Ruthotto

Common Coauthors

Coauthor	Papers Together
Maximilian März	10
Gitta Kutyniok	7
Martin Genzel	7
Stephan Wäldchen	5
Sascha Hauch	4
Luis Oala	3
Wojciech Samek	3
Amnon Drory	2
Rafael Reisenhofer	2
Melanie Weber	2
Gregory Naisat	2
Philipp Petersen	2
Christian Kümmerle	2
Sebastian Pokutta	2
Dennis Elbrächter	2
Danijel Kivaranovic	2
Jan Blechschmidt	2
Philipp Trunschke	2
Sebastian Lunz	2
Johannes von Lindheim	2
Jun-Da Sheng	2
Mathieu Besançon	2
Peter Hinz	2
Matteo Gambara	2
Nando Farchmin	2
Dominik Alfke	2
Ariel Neufeld	2
Ryan Malthaner	2
Silke Glas	2
Theophil Trippe	2
Philipp Grohs	2
Laura Thesing	2
David S. Weber	2
Mauricio J. del Razo Sarmina	2
Weston Baines	2
Cosmas Heiß	1
Lars Ruthotto	1
Ingo Gühring	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Deep Convolutional Neural Network for Inverse Problems in Imaging	2017	Kyong Hwan Jin Michael T. McCann Emmanuel Froustey Michaël Unser	4
+ PDF Chat	MoDL: Model-Based Deep Learning Architecture for Inverse Problems	2018	Hemant Kumar Aggarwal Merry Mani Mathews Jacob	3
+ PDF Chat	On instabilities of deep learning in image reconstruction and the potential costs of AI	2020	Vegard Antun Francesco Renna Clarice Poon Ben Adcock Anders C. Hansen	3
+ PDF Chat	Solving inverse problems using data-driven models	2019	Simon Arridge Peter Maaß Ozan Öktem Carola‐Bibiane Schönlieb	3
+ PDF Chat	Learned Primal-Dual Reconstruction	2018	Jonas Adler Ozan Öktem	3
+ PDF Chat	Learning the invisible: a hybrid deep learning-shearlet framework for limited angle computed tomography	2019	Tatiana A. Bubba Gitta Kutyniok Matti Lassas Maximilian März Wojciech Samek Samuli Siltanen Vignesh Srinivasan	3
+	A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction	2017	Eun‐Hee Kang Junhong Min Jong Chul Ye	3
+ PDF Chat	Densely Connected Convolutional Networks	2017	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	2
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	2
+ PDF Chat	Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network	2017	Hu Chen Yi Zhang Mannudeep K. Kalra Feng Lin Yang Chen Peixi Liao Jiliu Zhou Ge Wang	2
+ PDF Chat	Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge	2020	Florian Knöll Tullie Murrell Anuroop Sriram Nafissa Yakubova Jure Žbontar Michael Rabbat Aaron Defazio Matthew J. Muckley Daniel K. Sodickson C. Lawrence Zitnick	2
+	Deep Learning Techniques for Inverse Problems in Imaging	2020	Greg Ongie Ajil Jalal Christopher A. Metzler Richard G. Baraniuk Alexandros G. Dimakis Rebecca Willett	2
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	2
+	$Σ$-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction	2019	Kerstin Hammernik Jo Schlemper Chen Qin Jinming Duan Ronald M. Summers Daniel Rueckert	2
+ PDF Chat	State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge	2020	Matthew J. Muckley Bruno Riemenschneider Alireza Radmanesh Sunwoo Kim Geunu Jeong Jingyu Ko Yohan Jun Hyungseob Shin Dosik Hwang Mahmoud Mostapha	2
+ PDF Chat	Lightweight Probabilistic Deep Networks	2018	Jochen Gast Stefan Roth	2
+	The troublesome kernel: why deep learning for inverse problems is typically unstable.	2020	Nina Maria Gottschling Vegard Antun Ben Adcock Anders C. Hansen	2
+ PDF Chat	Solving Inverse Problems With Deep Neural Networks – Robustness Included?	2022	Martin Genzel Jan Macdonald Maximilian März	2
+ PDF Chat	The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation	2017	Simon Jégou Michal Drozdzal David Vázquez Adriana Romero Yoshua Bengio	2
+	Optimal Mass Transport for Registration and Warping	2004	Steven Haker Lei Zhu Allen Tannenbaum Sigurd Angenent	1
+	Approximation by superposition of sigmoidal and radial basis functions	1992	H. N. Mhaskar Charles A. Micchelli	1
+	On Alternating Direction Methods of Multipliers: A Historical Perspective	2014	Roland Glowinski	1
+	A tutorial on conformal prediction	2007	Glenn Shafer Vladimir Vovk	1
+ PDF Chat	Living on the edge: phase transitions in convex programs with random data	2014	Dennis Amelunxen Martin Lötz Michael B. McCoy Joel A. Tropp	1
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+	Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances	2011	Abbas Khosravi Saeid Nahavandi Douglas Creighton Amir F. Atiya	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Global Convergence of ADMM in Nonconvex Nonsmooth Optimization	2015	Yu Wang Wotao Yin Jinshan Zeng	1
+ PDF Chat	Evaluating the Visualization of What a Deep Neural Network Has Learned	2016	Wojciech Samek Alexander Binder Grégoire Montavon Sebastian Lapuschkin Klaus‐Robert Müller	1
+ PDF Chat	Sur l'approximation, par éléments finis d'ordre un, et la résolution, par pénalisation-dualité d'une classe de problèmes de Dirichlet non linéaires	1975	Roland Glowinski A. Marroco	1
+	Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	1
+	Statistical and Computational Inverse Problems	2006	Faming Liang Jianhua Huang	1
+ PDF Chat	Image Super-Resolution Using Deep Convolutional Networks	2015	Chao Dong Chen Change Loy Kaiming He Xiaoou Tang	1
+ PDF Chat	Compressive Classification and the Rare Eclipse Problem	2017	Afonso S. Bandeira Dustin G. Mixon Benjamin Recht	1
+ PDF Chat	Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information	2006	Emmanuel J. Candès Justin Romberg Terence Tao	1
+ PDF Chat	Speech recognition with deep recurrent neural networks	2013	Alex Graves Abdelrahman Mohamed Geoffrey E. Hinton	1
+ PDF Chat	Superreplication under volatility uncertainty for measurable claims	2013	Ariel Neufeld Marcel Nutz	1
+ PDF Chat	DeepPose: Human Pose Estimation via Deep Neural Networks	2014	Alexander Toshev Christian Szegedy	1
+ PDF Chat	Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring	2017	Seungjun Nah Tae Hyun Kim Kyoung Mu Lee	1
+	Training with Noise is Equivalent to Tikhonov Regularization	1995	Chris Bishop	1
+ PDF Chat	Deconvolution in Astronomy: A Review	2002	Jean‐Luc Starck Eric Pantin Fionn Murtagh	1
+	Distilling the Knowledge in a Neural Network	2015	Geoffrey E. Hinton Oriol Vinyals Jay B. Dean	1
+	A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction	2017	Jo Schlemper José Caballero Joseph V. Hajnal Anthony N. Price Daniel Rueckert	1
+	Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks	2016	Itay Safran Ohad Shamir	1
+	What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?	2017	Alex Kendall Yarin Gal	1
+	Learning a variational network for reconstruction of accelerated MRI data	2017	Kerstin Hammernik Teresa Klatzer Erich Kobler Michael P. Recht Daniel K. Sodickson Thomas Pock Florian Knöll	1
+	Learning Important Features Through Propagating Activation Differences	2017	Avanti Shrikumar Peyton Greenside Anshul Kundaje	1
+ PDF Chat	Image reconstruction by domain-transform manifold learning	2018	Bo Zhu Jeremiah Zhe Liu Stephen Cauley Bruce R. Rosen Matthew S. Rosen	1
+	Recurrent Inference Machines for Solving Inverse Problems	2017	Patrick Putzky Max Welling	1
+ PDF Chat	Error bounds for approximations with deep ReLU networks	2017	Dmitry Yarotsky	1