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PCA Reduced Gaussian Mixture Models with Applications in Superresolution

PCA Reduced Gaussian Mixture Models with Applications in Superresolution

16 September 2020
J. Hertrich
D. Nguyen
Jean-François Aujol
Dominique Bernard
Y. Berthoumieu
Abdellativ Saadaldin
Gabriele Steidl
ArXivPDFHTML

Papers citing "PCA Reduced Gaussian Mixture Models with Applications in Superresolution"

5 / 5 papers shown
Title
Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters
Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters
Sebastian Salwig
Till Kahlke
F. Hirschberger
D. Forster
Jorg Lucke
VLM
82
0
0
21 Jan 2025
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
24
6
0
27 Dec 2023
Pluto's Surface Mapping using Unsupervised Learning from Near-Infrared
  Observations of LEISA/Ralph
Pluto's Surface Mapping using Unsupervised Learning from Near-Infrared Observations of LEISA/Ralph
A. Emran
C. D. Dalle Ore
C. Ahrens
M. K. H. Khan
V. Chevrier
D. Cruikshank
36
4
0
15 Jan 2023
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for
  Superresolution
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution
Fabian Altekrüger
J. Hertrich
25
15
0
20 Jan 2022
On EM algorithms and their proximal generalizations
On EM algorithms and their proximal generalizations
Stéphane Chrétien
Alfred Hero
FedML
60
47
0
27 Jan 2012
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