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End-to-end reconstruction meets data-driven regularization for inverse
  problems

End-to-end reconstruction meets data-driven regularization for inverse problems

7 June 2021
Subhadip Mukherjee
M. Carioni
Ozan Oktem
Carola-Bibiane Schönlieb
ArXiv (abs)PDFHTML

Papers citing "End-to-end reconstruction meets data-driven regularization for inverse problems"

26 / 26 papers shown
Title
Towards Prospective Medical Image Reconstruction via Knowledge-Informed Dynamic Optimal Transport
Taoran Zheng
Xing Li
Yan Yang
Xiang Gu
Zongben Xu
Jian Sun
MedIm
74
0
0
23 May 2025
CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping
CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping
Xiaojian Xu
Weijie Gan
Satya V. V. N. Kothapalli
D. Yablonskiy
Ulugbek S. Kamilov
MedIm
141
5
0
21 Feb 2025
Swap-Net: A Memory-Efficient 2.5D Network for Sparse-View 3D Cone Beam
  CT Reconstruction
Swap-Net: A Memory-Efficient 2.5D Network for Sparse-View 3D Cone Beam CT Reconstruction
Xiaojian Xu
Marc Klasky
Michael T. McCann
Jason Hu
Jeffrey A. Fessler
3DPCMedIm
56
0
0
29 Sep 2024
Neural Incremental Data Assimilation
Neural Incremental Data Assimilation
Matthieu Blanke
Ronan Fablet
Marc Lelarge
AI4CE
66
1
0
21 Jun 2024
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse
  Problems
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems
Rafael Orozco
Ali Siahkoohi
M. Louboutin
Felix J. Herrmann
72
2
0
08 May 2024
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Hongwei Tan
Ziruo Cai
Marcelo Pereyra
Subhadip Mukherjee
Junqi Tang
Carola-Bibiane Schönlieb
SSL
95
1
0
08 Apr 2024
QN-Mixer: A Quasi-Newton MLP-Mixer Model for Sparse-View CT
  Reconstruction
QN-Mixer: A Quasi-Newton MLP-Mixer Model for Sparse-View CT Reconstruction
Ishak Ayad
Nicolas Larue
Mai K. Nguyen
73
4
0
28 Feb 2024
Debiasing Machine Learning Models by Using Weakly Supervised Learning
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
62
1
0
23 Feb 2024
Robustness and Exploration of Variational and Machine Learning
  Approaches to Inverse Problems: An Overview
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview
Alexander Auras
Kanchana Vaishnavi Gandikota
Hannah Droege
Michael Moeller
AAML
72
0
0
19 Feb 2024
Learned reconstruction methods for inverse problems: sample error
  estimates
Learned reconstruction methods for inverse problems: sample error estimates
Luca Ratti
60
0
0
21 Dec 2023
Unsupervised approaches based on optimal transport and convex analysis
  for inverse problems in imaging
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging
M. Carioni
Subhadip Mukherjee
Hongwei Tan
Junqi Tang
MedIm
78
4
0
15 Nov 2023
What's in a Prior? Learned Proximal Networks for Inverse Problems
What's in a Prior? Learned Proximal Networks for Inverse Problems
Zhenghan Fang
Sam Buchanan
Jeremias Sulam
86
12
0
22 Oct 2023
Provably Convergent Data-Driven Convex-Nonconvex Regularization
Provably Convergent Data-Driven Convex-Nonconvex Regularization
Zakhar Shumaylov
Jeremy Budd
Subhadip Mukherjee
Carola-Bibiane Schönlieb
102
5
0
09 Oct 2023
LCOT: Linear circular optimal transport
LCOT: Linear circular optimal transport
Rocio Diaz Martin
Ivan Medri
Yikun Bai
Xinran Liu
Kangbai Yan
Gustavo K. Rohde
Soheil Kolouri
53
1
0
09 Oct 2023
Solving Low-Dose CT Reconstruction via GAN with Local Coherence
Solving Low-Dose CT Reconstruction via GAN with Local Coherence
Wenjie Liu
MedIm
23
2
0
24 Sep 2023
Learning end-to-end inversion of circular Radon transforms in the
  partial radial setup
Learning end-to-end inversion of circular Radon transforms in the partial radial setup
Deep Ray
Souvik Roy
48
0
0
27 Aug 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging
  Inverse Problems
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
Ziruo Cai
Junqi Tang
Subhadip Mukherjee
Jinglai Li
Carola Bibiane Schönlieb
Xiaoqun Zhang
AI4CE
67
4
0
17 Apr 2023
Learned Interferometric Imaging for the SPIDER Instrument
Learned Interferometric Imaging for the SPIDER Instrument
Matthijs Mars
M. Betcke
Jason D. McEwen
47
3
0
24 Jan 2023
A new method for determining Wasserstein 1 optimal transport maps from
  Kantorovich potentials, with deep learning applications
A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications
Tristan Milne
Étienne Bilocq
A. Nachman
OT
76
3
0
02 Nov 2022
Estimating a potential without the agony of the partition function
Estimating a potential without the agony of the partition function
E. Haber
Moshe Eliasof
L. Tenorio
61
2
0
19 Aug 2022
Learned reconstruction methods with convergence guarantees
Learned reconstruction methods with convergence guarantees
Subhadip Mukherjee
A. Hauptmann
Ozan Oktem
Marcelo Pereyra
Carola-Bibiane Schönlieb
87
51
0
11 Jun 2022
Online Deep Equilibrium Learning for Regularization by Denoising
Online Deep Equilibrium Learning for Regularization by Denoising
Jiaming Liu
Xiaojian Xu
Weijie Gan
Shirin Shoushtari
Ulugbek S. Kamilov
112
27
0
25 May 2022
PatchNR: Learning from Very Few Images by Patch Normalizing Flow
  Regularization
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization
Fabian Altekrüger
Alexander Denker
Paul Hagemann
J. Hertrich
Peter Maass
Gabriele Steidl
MedIm
84
27
0
24 May 2022
Trust the Critics: Generatorless and Multipurpose WGANs with Initial
  Convergence Guarantees
Trust the Critics: Generatorless and Multipurpose WGANs with Initial Convergence Guarantees
Tristan Milne
Étienne Bilocq
A. Nachman
31
3
0
30 Nov 2021
Stochastic Primal-Dual Deep Unrolling
Stochastic Primal-Dual Deep Unrolling
Junqi Tang
Subhadip Mukherjee
Carola-Bibiane Schönlieb
96
4
0
19 Oct 2021
Deep Bayesian inference for seismic imaging with tasks
Deep Bayesian inference for seismic imaging with tasks
Ali Siahkoohi
G. Rizzuti
Felix J. Herrmann
BDLUQCV
97
21
0
10 Oct 2021
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