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2002.11821
Cited By
Improving Robustness of Deep-Learning-Based Image Reconstruction
International Conference on Machine Learning (ICML), 2020
26 February 2020
Ankit Raj
Y. Bresler
Yue Liu
OOD
AAML
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Papers citing
"Improving Robustness of Deep-Learning-Based Image Reconstruction"
24 / 24 papers shown
Adversarial generalization of unfolding (model-based) networks
Vicky Kouni
AAML
322
0
0
18 Sep 2025
Hallucinations in medical devices
Jason Granstedt
Prabhat Kc
Rucha Deshpande
Victor Garcia
Aldo Badano
196
5
0
18 Aug 2025
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview
Alexander Auras
Kanchana Vaishnavi Gandikota
Hannah Droege
Michael Moeller
AAML
273
1
0
19 Feb 2024
Evaluating Adversarial Robustness of Low dose CT Recovery
Kanchana Vaishnavi Gandikota
Paramanand Chandramouli
Hannah Dröge
Michael Moeller
OOD
AAML
205
3
0
18 Feb 2024
Do stable neural networks exist for classification problems? -- A new view on stability in AI
Z. N. D. Liu
A. C. Hansen
219
4
0
15 Jan 2024
Data-iterative Optimization Score Model for Stable Ultra-Sparse-View CT Reconstruction
Weiwen Wu
Yanyang Wang
DiffM
143
8
0
28 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering
Neural Information Processing Systems (NeurIPS), 2023
Anselm Krainovic
Mahdi Soltanolkotabi
Reinhard Heckel
OOD
143
9
0
24 Jul 2023
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Astha Verma
A. Subramanyam
Siddhesh Bangar
Naman Lal
R. Shah
Shiníchi Satoh
327
8
0
13 Apr 2023
Adversarial Attack and Defense for Medical Image Analysis: Methods and Applications
ACM Computing Surveys (ACM Comput. Surv.), 2023
Junhao Dong
Junxi Chen
Xiaohua Xie
Jianhuang Lai
Hechang Chen
AAML
MedIm
347
10
0
24 Mar 2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Yuguang Yao
Jiancheng Liu
Yifan Gong
Xiaoming Liu
Yanzhi Wang
Xinyu Lin
Sijia Liu
AAML
MLAU
324
1
0
13 Mar 2023
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality
International Conference on Machine Learning (ICML), 2022
Guy Ohayon
Theo Adrai
Michael Elad
T. Michaeli
AAML
267
18
0
16 Nov 2022
On Adversarial Robustness of Deep Image Deblurring
International Conference on Information Photonics (ICIP), 2022
Kanchana Vaishnavi Gandikota
Paramanand Chandramouli
Michael Moeller
202
13
0
05 Oct 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
International Conference on Learning Representations (ICLR), 2022
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
351
40
0
27 Mar 2022
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learning
Arjun D Desai
Batu Mehmet Ozturkler
Christopher M. Sandino
R. Boutin
M. Willis
S. Vasanawala
B. Hargreaves
Christopher Ré
John M. Pauly
Akshay S. Chaudhari
464
3
0
30 Sep 2021
A review and experimental evaluation of deep learning methods for MRI reconstruction
Arghya Pal
Yogesh Rathi
3DV
353
57
0
17 Sep 2021
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results
Efrat Shimron
Jonathan I. Tamir
Ke Wang
Michael Lustig
AI4CE
227
11
0
16 Sep 2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations
Fangqiu Yi
Jinghan Jia
Burhaneddin Yaman
S. Moeller
Sijia Liu
Mingyi Hong
Mehmet Akçakaya
AAML
140
8
0
25 Feb 2021
Center Smoothing: Certified Robustness for Networks with Structured Outputs
Neural Information Processing Systems (NeurIPS), 2021
Aounon Kumar
Tom Goldstein
OOD
AAML
UQCV
248
20
0
19 Feb 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging
IEEE Transactions on Computational Imaging (IEEE Trans. Comput. Imaging), 2021
Davis Gilton
Greg Ongie
Rebecca Willett
242
224
0
16 Feb 2021
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2021
Matthew J. Colbrook
Vegard Antun
A. Hansen
431
151
0
20 Jan 2021
Model Adaptation for Inverse Problems in Imaging
IEEE Transactions on Computational Imaging (TCI), 2020
Davis Gilton
Greg Ongie
Rebecca Willett
OOD
MedIm
475
53
0
30 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included?
Martin Genzel
Jan Macdonald
M. März
AAML
OOD
191
131
0
09 Nov 2020
Interval Neural Networks as Instability Detectors for Image Reconstructions
Bildverarbeitung für die Medizin (BVM), 2020
Jan Macdonald
M. März
Luis Oala
Wojciech Samek
160
2
0
27 Mar 2020
The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems
SIAM Review (SIAM Rev.), 2020
N. Gottschling
Vegard Antun
A. Hansen
Ben Adcock
501
54
0
05 Jan 2020
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