Model Adaptation for Inverse Problems in Imaging

30 November 2020

Papers citing "Model Adaptation for Inverse Problems in Imaging"

20 / 20 papers shown

Title
Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models Shirin Shoushtari Edward P. Chandler M. Salman Asif Ulugbek S. Kamilov DiffM 28 0 0 16 May 2025
Towards Robust and Generalizable Lensless Imaging with Modular Learned Reconstruction Eric Bezzam Yohann Perron M. Vetterli 59 0 0 03 Feb 2025
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems Eric Chen Xi Chen A. Maleki S. Jalali 45 0 0 08 Jan 2025
Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures Peimeng Guan Naveed Iqbal Mark A. Davenport Mudassir Masood 50 2 0 07 Mar 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 41 0 0 19 Feb 2024
Tell Me What You See: Text-Guided Real-World Image Denoising E. Yosef Raja Giryes DiffM 59 2 0 15 Dec 2023
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency Bowen Song Soo Min Kwon Zecheng Zhang Xinyu Hu Qing Qu Liyue Shen MedIm 44 105 0 16 Jul 2023
PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction F. Zimmermann C. Kolbitsch Patrick Schuenke A. Kofler 31 5 0 19 Jun 2023
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts Jian Liang Ran He Tien-Ping Tan OOD VLM TTA 54 209 0 27 Mar 2023
Differentiable Uncalibrated Imaging Sidharth Gupta K. Kothari Valentin Debarnot Ivan Dokmanić MedIm 37 4 0 18 Nov 2022
Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model Jun-Hao Hu Shirin Shoushtari Zihao Zou Jiaming Liu Zhixin Sun Ulugbek S. Kamilov 64 4 0 01 Nov 2022
Deep Model-Based Architectures for Inverse Problems under Mismatched Priors Shirin Shoushtari Jiaming Liu Yuyang Hu Ulugbek S. Kamilov 28 6 0 26 Jul 2022
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning Martin Genzel Ingo Gühring Jan Macdonald M. März 38 25 0 14 Jun 2022
Connections between Deep Equilibrium and Sparse Representation Models with Application to Hyperspectral Image Denoising A. Gkillas D. Ampeliotis K. Berberidis 34 15 0 29 Mar 2022
Training Adaptive Reconstruction Networks for Blind Inverse Problems Alban Gossard P. Weiss MedIm 34 5 0 23 Feb 2022
A Field of Experts Prior for Adapting Neural Networks at Test Time Neerav Karani G. Brunner Ertunc Erdil Simin Fei K. Tezcan K. Chaitanya E. Konukoglu OOD 26 2 0 10 Feb 2022
An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction Riccardo Barbano Johannes Leuschner Maximilian Schmidt Alexander Denker A. Hauptmann Peter Maass Bangti Jin 48 19 0 23 Nov 2021
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution Yunshi Huang Émilie Chouzenoux J. Pesquet BDL 29 12 0 14 Oct 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
Regularization by Denoising: Clarifications and New Interpretations E. T. Reehorst Philip Schniter 56 215 0 06 Jun 2018