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2205.12021
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PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization
Inverse Problems (IP), 2022
24 May 2022
Fabian Altekrüger
Alexander Denker
Paul Hagemann
J. Hertrich
Peter Maass
Gabriele Steidl
MedIm
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Papers citing
"PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization"
17 / 17 papers shown
Learning Regularization Functionals for Inverse Problems: A Comparative Study
J. Hertrich
Matthias Joachim Ehrhardt
Alexander Denker
Stanislas Ducotterd
Zhenghan Fang
...
German Shâma Wache
Martin Zach
Yasi Zhang
Matthias Joachim Ehrhardt
Sebastian Neumayer
234
10
0
02 Oct 2025
MoiréXNet: Adaptive Multi-Scale Demoiréing with Linear Attention Test-Time Training and Truncated Flow Matching Prior
Liangyan Li
Yimo Ning
Kevin Le
Wei Dong
Yunzhe Li
Jun Chen
Xiaohong Liu
306
0
0
19 Jun 2025
Unsupervised Low-dose CT Reconstruction with One-way Conditional Normalizing Flows
IEEE Transactions on Computational Imaging (TCI), 2024
Ran An
Ke Chen
Hongwei Li
OOD
298
1
0
23 Oct 2024
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
International Conference on Learning Representations (ICLR), 2024
Ségolène Martin
Anne Gagneux
Paul Hagemann
Gabriele Steidl
620
71
0
03 Oct 2024
Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning
P. Milanfar
M. Delbracio
AI4CE
514
37
0
10 Sep 2024
T-FAKE: Synthesizing Thermal Images for Facial Landmarking
Computer Vision and Pattern Recognition (CVPR), 2024
Philipp Flotho
Moritz Piening
Anna Kukleva
Gabriele Steidl
482
6
0
27 Aug 2024
A Low-dose CT Reconstruction Network Based on TV-regularized OSEM Algorithm
Ran An
Yinghui Zhang
Xi Chen
Lemeng Li
Ke Chen
Hongwei Li
159
0
0
25 Aug 2024
Stability of Data-Dependent Ridge-Regularization for Inverse Problems
Sebastian Neumayer
Fabian Altekrüger
497
5
0
18 Jun 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
289
1
0
19 Feb 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction
Moritz Piening
Fabian Altekrüger
J. Hertrich
Paul Hagemann
Andrea Walther
Gabriele Steidl
307
9
0
27 Dec 2023
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
International Conference on Learning Representations (ICLR), 2023
Paul Hagemann
J. Hertrich
Fabian Altekrüger
Robert Beinert
Jannis Chemseddine
Gabriele Steidl
477
31
0
04 Oct 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
SIAM Journal of Imaging Sciences (JSIS), 2023
Ziruo Cai
Junqi Tang
Subhadip Mukherjee
Jinglai Li
Carola Bibiane Schönlieb
Xiaoqun Zhang
AI4CE
271
8
0
17 Apr 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
Fabian Altekrüger
Paul Hagemann
Gabriele Steidl
TPM
385
11
0
28 Mar 2023
Manifold Learning by Mixture Models of VAEs for Inverse Problems
Journal of machine learning research (JMLR), 2023
Giovanni S. Alberti
J. Hertrich
Matteo Santacesaria
Silvia Sciutto
DRL
474
13
0
27 Mar 2023
Inverse problem regularization with hierarchical variational autoencoders
IEEE International Conference on Computer Vision (ICCV), 2023
Jean Prost
Antoine Houdard
Andrés Almansa
Nicolas Papadakis
387
10
0
20 Mar 2023
Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation
Paul Hagemann
Sophie Mildenberger
Lars Ruthotto
Gabriele Steidl
Ni Yang
DiffM
507
38
0
08 Mar 2023
Training Adaptive Reconstruction Networks for Blind Inverse Problems
SIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2022
Alban Gossard
P. Weiss
MedIm
480
11
0
23 Feb 2022
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