Improving Robustness of Deep-Learning-Based Image Reconstruction

26 February 2020

Papers citing "Improving Robustness of Deep-Learning-Based Image Reconstruction"

24 / 24 papers shown

Title
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview Alexander Auras Kanchana Vaishnavi Gandikota Hannah Droege Michael Moeller AAML 31 0 0 19 Feb 2024
Evaluating Adversarial Robustness of Low dose CT Recovery Kanchana Vaishnavi Gandikota Paramanand Chandramouli Hannah Dröge Michael Moeller OOD AAML 37 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 30 0 0 15 Jan 2024
Data-iterative Optimization Score Model for Stable Ultra-Sparse-View CT Reconstruction Weiwen Wu Yanyang Wang DiffM 27 7 0 28 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering Anselm Krainovic Mahdi Soltanolkotabi Reinhard Heckel OOD 22 6 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 42 4 0 13 Apr 2023
Adversarial Attack and Defense for Medical Image Analysis: Methods and Applications Junhao Dong Junxi Chen Xiaohua Xie Jianhuang Lai H. Chen AAML MedIm 35 16 0 24 Mar 2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information? Yuguang Yao Jiancheng Liu Yifan Gong Xiaoming Liu Yanzhi Wang X. Lin Sijia Liu AAML MLAU 29 1 0 13 Mar 2023
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality Guy Ohayon Theo Adrai Michael Elad T. Michaeli AAML 37 13 0 16 Nov 2022
On Adversarial Robustness of Deep Image Deblurring Kanchana Vaishnavi Gandikota Paramanand Chandramouli Michael Moeller 39 11 0 05 Oct 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 26 33 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 27 3 0 30 Sep 2021
A review and experimental evaluation of deep learning methods for MRI reconstruction Arghya Pal Yogesh Rathi 3DV 47 41 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 21 11 0 16 Sep 2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations Chi Zhang Jinghan Jia Burhaneddin Yaman S. Moeller Sijia Liu Mingyi Hong Mehmet Akçakaya AAML 19 8 0 25 Feb 2021
Center Smoothing: Certified Robustness for Networks with Structured Outputs Aounon Kumar Tom Goldstein OOD AAML UQCV 15 19 0 19 Feb 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 49 181 0 16 Feb 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 73 130 0 20 Jan 2021
Model Adaptation for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett OOD MedIm 16 48 0 30 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 27 101 0 09 Nov 2020
Interval Neural Networks as Instability Detectors for Image Reconstructions Jan Macdonald M. März Luis Oala Wojciech Samek 28 2 0 27 Mar 2020
The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problems N. Gottschling Vegard Antun A. Hansen Ben Adcock 24 31 0 05 Jan 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,112 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,842 0 08 Jul 2016