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PatchNR: Learning from Very Few Images by Patch Normalizing Flow
  Regularization

PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization

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"

5 / 5 papers shown
Title
Learning from small data sets: Patch-based regularizers in inverse
  problems for image reconstruction
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
19
5
0
27 Dec 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees
  for Bayesian Inverse Problems
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
Fabian Altekrüger
Paul Hagemann
Gabriele Steidl
TPM
16
9
0
28 Mar 2023
Denoising Diffusion Restoration Models
Denoising Diffusion Restoration Models
Bahjat Kawar
Michael Elad
Stefano Ermon
Jiaming Song
DiffM
204
770
0
27 Jan 2022
Posterior Sampling for Image Restoration using Explicit Patch Priors
Posterior Sampling for Image Restoration using Explicit Patch Priors
Roy Friedman
Yair Weiss
30
5
0
20 Apr 2021
Solving Inverse Problems with a Flow-based Noise Model
Solving Inverse Problems with a Flow-based Noise Model
Jay Whang
Qi Lei
A. Dimakis
56
36
0
18 Mar 2020
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