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WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for
  Superresolution
v1v2v3 (latest)

WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution

SIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2022
20 January 2022
Fabian Altekrüger
J. Hertrich
ArXiv (abs)PDFHTML

Papers citing "WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution"

10 / 10 papers shown
T-FAKE: Synthesizing Thermal Images for Facial Landmarking
T-FAKE: Synthesizing Thermal Images for Facial LandmarkingComputer Vision and Pattern Recognition (CVPR), 2024
Philipp Flotho
Moritz Piening
Anna Kukleva
Gabriele Steidl
480
6
0
27 Aug 2024
Importance Corrected Neural JKO Sampling
Importance Corrected Neural JKO Sampling
Johannes Hertrich
Robert Gruhlke
520
7
0
29 Jul 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
289
1
0
19 Feb 2024
Mixed Noise and Posterior Estimation with Conditional DeepGEM
Mixed Noise and Posterior Estimation with Conditional DeepGEM
Paul Hagemann
J. Hertrich
Maren Casfor
Sebastian Heidenreich
Gabriele Steidl
347
1
0
05 Feb 2024
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
300
9
0
27 Dec 2023
Equivariant Bootstrapping for Uncertainty Quantification in Imaging
  Inverse Problems
Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse ProblemsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Julian Tachella
Marcelo Pereyra
UQCV
262
15
0
18 Oct 2023
Posterior Sampling Based on Gradient Flows of the MMD with Negative
  Distance Kernel
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance KernelInternational Conference on Learning Representations (ICLR), 2023
Paul Hagemann
J. Hertrich
Fabian Altekrüger
Robert Beinert
Jannis Chemseddine
Gabriele Steidl
476
31
0
04 Oct 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
384
11
0
28 Mar 2023
PatchNR: Learning from Very Few Images by Patch Normalizing Flow
  Regularization
PatchNR: Learning from Very Few Images by Patch Normalizing Flow RegularizationInverse Problems (IP), 2022
Fabian Altekrüger
Alexander Denker
Paul Hagemann
J. Hertrich
Peter Maass
Gabriele Steidl
MedIm
404
30
0
24 May 2022
Generalized Normalizing Flows via Markov Chains
Generalized Normalizing Flows via Markov Chains
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDLDiffMAI4CE
526
27
0
24 Nov 2021
1
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