To be or not to be stable, that is the question: understanding neural
networks for inverse problems

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To be or not to be stable, that is the question: understanding neural networks for inverse problems

24 November 2022

David Evangelista

E. L. Piccolomini

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Papers citing "To be or not to be stable, that is the question: understanding neural networks for inverse problems"

15 / 15 papers shown

Title
Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations Jan Nikolas Morshuis S. Gatidis Matthias Hein Christian F. Baumgartner AAML OOD 75 13 0 05 Aug 2022
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI Thomas Yu T. Hilbert G. Piredda Arun A. Joseph G. Bonanno ... P. Omoumi Meritxell Bach Cuadra Erick Jorge Canales-Rodríguez Thomas Kober Jean-Philippe Thiran 60 5 0 29 Jan 2022
A review and experimental evaluation of deep learning methods for MRI reconstruction Arghya Pal Yogesh Rathi 3DV 68 44 0 17 Sep 2021
The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks Alexander Bastounis A. Hansen Verner Vlacic AAML OOD 83 28 0 13 Sep 2021
Data augmentation for deep learning based accelerated MRI reconstruction with limited data Zalan Fabian Reinhard Heckel Mahdi Soltanolkotabi OOD MedIm 46 51 0 28 Jun 2021
The Modern Mathematics of Deep Learning Julius Berner Philipp Grohs Gitta Kutyniok P. Petersen 43 116 0 09 May 2021
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem Matthew J. Colbrook Vegard Antun A. Hansen 114 135 0 20 Jan 2021
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 54 107 0 09 Nov 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 88 134 0 22 Sep 2020
The gap between theory and practice in function approximation with deep neural networks Ben Adcock N. Dexter 57 94 0 16 Jan 2020
On instabilities of deep learning in image reconstruction - Does AI come at a cost? Vegard Antun F. Renna C. Poon Ben Adcock A. Hansen 59 605 0 14 Feb 2019
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring Seungjun Nah Tae Hyun Kim Kyoung Mu Lee 147 1,980 0 07 Dec 2016
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 154 4,905 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 282 14,963 1 21 Dec 2013