Solving Inverse Problems With Deep Neural Networks -- Robustness Included?

9 November 2020

Papers citing "Solving Inverse Problems With Deep Neural Networks -- Robustness Included?"

46 / 46 papers shown

Title
An incremental algorithm for non-convex AI-enhanced medical image processing Elena Morotti 34 0 0 13 May 2025
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers Elad Sofer Tomer Shaked Caroline Chaux Nir Shlezinger AAML 45 0 0 26 Apr 2025
Stability Bounds for the Unfolded Forward-Backward Algorithm Émilie Chouzenoux Cecile Della Valle J. Pesquet 26 0 0 23 Dec 2024
Intensity Field Decomposition for Tissue-Guided Neural Tomography Meng-Xun Li Jin-Gang Yu Yuan Gao Cui Huang Gui-Song Xia 3DV 70 0 0 01 Nov 2024
Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating the Accuracy-Robustness Tradeoff Peimeng Guan Mark A. Davenport 28 0 0 18 Oct 2024
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning Frederik Hoppe C. M. Verdun Hannah Laus Felix Krahmer Holger Rauhut UQCV 22 1 0 18 Jul 2024
LIP-CAR: contrast agent reduction by a deep learned inverse problem Davide Bianchi Sonia Colombo Serra Davide Evangelista Pengpeng Luo E. Morotti Giovanni Valbusa MedIm 22 0 0 15 Jul 2024
Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey Lei Li J. Camps Blanca Rodriguez Vicente Grau SyDa 38 2 0 17 Jun 2024
Debiasing Machine Learning Models by Using Weakly Supervised Learning Renan D. B. Brotto Jean-Michel Loubes Laurent Risser J. Florens K. Filho João Marcos Travassos Romano 34 0 0 23 Feb 2024
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 23 3 0 18 Feb 2024
Local monotone operator learning using non-monotone operators: MnM-MOL Maneesh John Jyothi Rikabh Chand Mathews Jacob 16 1 0 01 Dec 2023
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers M. Terris Thomas Moreau 24 0 0 30 Nov 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering Anselm Krainovic Mahdi Soltanolkotabi Reinhard Heckel OOD 22 6 0 24 Jul 2023
Evaluating Similitude and Robustness of Deep Image Denoising Models via Adversarial Attack Jie Ning Jiebao Sun Yao Li Zhichang Guo Wangmeng Zuo 9 6 0 28 Jun 2023
Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction Christoph Angermann Simon Göppel Markus Haltmeier 28 2 0 14 Apr 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 23 9 0 28 Mar 2023
A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems Haocheng Ju Haimiao Zhang Lin Li Xiao Li B. Dong BDL 22 2 0 07 Mar 2023
Representing Noisy Image Without Denoising Shuren Qi Yushu Zhang Chao Wang Tao Xiang Xiaochun Cao Yong Xiang 13 1 0 18 Jan 2023
On the Robustness of Normalizing Flows for Inverse Problems in Imaging Seongmin Hong I. Park S. Chun 23 7 0 08 Dec 2022
To be or not to be stable, that is the question: understanding neural networks for inverse problems David Evangelista J. Nagy E. Morotti E. L. Piccolomini 23 4 0 24 Nov 2022
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images Theophil Trippe Martin Genzel Jan Macdonald M. März 26 1 0 18 Nov 2022
Using explainability to design physics-aware CNNs for solving subsurface inverse problems J. Crocker Krishna Kumar B. Cox 17 9 0 16 Nov 2022
Data Models for Dataset Drift Controls in Machine Learning With Optical Images Luis Oala Marco Aversa Gabriel Nobis Kurt Willis Yoan Neuenschwander ... E. Pomarico Wojciech Samek Roderick Murray-Smith Christoph Clausen B. Sanguinetti 23 5 0 04 Nov 2022
On Adversarial Robustness of Deep Image Deblurring Kanchana Vaishnavi Gandikota Paramanand Chandramouli Michael Moeller 31 11 0 05 Oct 2022
Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations Jan Nikolas Morshuis S. Gatidis Matthias Hein Christian F. Baumgartner AAML OOD 14 13 0 05 Aug 2022
Stability of Image-Reconstruction Algorithms Pol del Aguila Pla Sebastian Neumayer M. Unser 8 10 0 14 Jun 2022
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning Martin Genzel Ingo Gühring Jan Macdonald M. März 25 25 0 14 Jun 2022
Learned reconstruction methods with convergence guarantees Subhadip Mukherjee A. Hauptmann Ozan Oktem Marcelo Pereyra Carola-Bibiane Schönlieb 22 49 0 11 Jun 2022
Localized adversarial artifacts for compressed sensing MRI Rima Alaifari Giovanni S. Alberti Tandri Gauksson AAML 14 4 0 10 Jun 2022
Memory-efficient model-based deep learning with convergence and robustness guarantees Aniket Pramanik M. Zimmerman M. Jacob 3DV 11 13 0 06 Jun 2022
Deep neural networks can stably solve high-dimensional, noisy, non-linear inverse problems Andrés Felipe Lerma Pineda P. Petersen 21 5 0 02 Jun 2022
NESTANets: Stable, accurate and efficient neural networks for analysis-sparse inverse problems Maksym Neyra-Nesterenko Ben Adcock 25 9 0 02 Mar 2022
Training Adaptive Reconstruction Networks for Blind Inverse Problems Alban Gossard P. Weiss MedIm 24 5 0 23 Feb 2022
Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery Jonathan Sauder Martin Genzel P. Jung 19 1 0 07 Feb 2022
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results Efrat Shimron Jonathan I. Tamir Ke Wang Michael Lustig AI4CE 11 11 0 16 Sep 2021
Regularizing Instabilities in Image Reconstruction Arising from Learned Denoisers Abinash Nayak 16 0 0 21 Aug 2021
Connections between Numerical Algorithms for PDEs and Neural Networks Tobias Alt Karl Schrader M. Augustin Pascal Peter Joachim Weickert PINN 21 21 0 30 Jul 2021
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry Martin Genzel Jan Macdonald M. März 10 4 0 01 Jun 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 14 8 0 25 Feb 2021
Deep Equilibrium Architectures for Inverse Problems in Imaging Davis Gilton Greg Ongie Rebecca Willett 38 180 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 70 129 0 20 Jan 2021
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
Solving Traveltime Tomography with Deep Learning Yuwei Fan Lexing Ying 14 13 0 25 Nov 2019
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 281 5,835 0 08 Jul 2016
Near-optimal compressed sensing guarantees for total variation minimization Deanna Needell Rachel A. Ward 46 89 0 11 Oct 2012