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Approximate Message Passing with Restricted Boltzmann Machine Priors
v1v2v3 (latest)

Approximate Message Passing with Restricted Boltzmann Machine Priors

23 February 2015
Eric W. Tramel
Angélique Dremeau
Florent Krzakala
ArXiv (abs)PDFHTML

Papers citing "Approximate Message Passing with Restricted Boltzmann Machine Priors"

14 / 14 papers shown
Compressed Sensing via Measurement-Conditional Generative Models
Compressed Sensing via Measurement-Conditional Generative Models
Kyungsu Kim
J. H. Lee
Eunho Yang
GANMedIm
270
3
0
02 Jul 2020
Exact asymptotics for phase retrieval and compressed sensing with random
  generative priors
Exact asymptotics for phase retrieval and compressed sensing with random generative priorsMathematical and Scientific Machine Learning (MSML), 2019
Benjamin Aubin
Bruno Loureiro
Antoine Baker
Florent Krzakala
Lenka Zdeborová
364
39
0
04 Dec 2019
Mean-field inference methods for neural networks
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
422
37
0
03 Nov 2019
Tree Search Network for Sparse Regression
Tree Search Network for Sparse Regression
Kyung-Su Kim
Sae-Young Chung
207
1
0
01 Apr 2019
Rate-Adaptive Neural Networks for Spatial Multiplexers
Rate-Adaptive Neural Networks for Spatial Multiplexers
Suhas Lohit
Rajhans Singh
K. Kulkarni
Pavan Turaga
189
17
0
08 Sep 2018
A relativistic extension of Hopfield neural networks via the mechanical
  analogy
A relativistic extension of Hopfield neural networks via the mechanical analogy
Adriano Barra
M. Beccaria
A. Fachechi
187
3
0
05 Jan 2018
Exploiting Restricted Boltzmann Machines and Deep Belief Networks in
  Compressed Sensing
Exploiting Restricted Boltzmann Machines and Deep Belief Networks in Compressed SensingIEEE Transactions on Signal Processing (IEEE TSP), 2017
Luisa F. Polanía
Kenneth Barner
189
30
0
30 May 2017
Learned D-AMP: Principled Neural Network based Compressive Image
  Recovery
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Christopher A. Metzler
Ali Mousavi
Richard G. Baraniuk
472
309
0
21 Apr 2017
A Deterministic and Generalized Framework for Unsupervised Learning with
  Restricted Boltzmann Machines
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann MachinesPhysical Review X (PRX), 2017
Eric W. Tramel
Marylou Gabrié
Andre Manoel
F. Caltagirone
Florent Krzakala
AI4CE
359
33
0
10 Feb 2017
A Variational Bayesian Approach for Image Restoration. Application to
  Image Deblurring with Poisson-Gaussian Noise
A Variational Bayesian Approach for Image Restoration. Application to Image Deblurring with Poisson-Gaussian Noise
Y. Marnissi
Yuling Zheng
Émilie Chouzenoux
J. Pesquet
352
42
0
24 Oct 2016
Proceedings of the third "international Traveling Workshop on
  Interactions between Sparse models and Technology" (iTWIST'16)
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16)
V. Abrol
O. Absil
P.-A. Absil
S. Anthoine
P. Antoine
...
D. Vukobratović
Li Wang
B. Wirth
Gerhard Wunder
Hongyan Zhang
207
0
0
14 Sep 2016
Inferring Sparsity: Compressed Sensing using Generalized Restricted
  Boltzmann Machines
Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines
Eric W. Tramel
Andre Manoel
F. Caltagirone
Marylou Gabrié
Florent Krzakala
256
22
0
13 Jun 2016
Statistical physics of inference: Thresholds and algorithms
Statistical physics of inference: Thresholds and algorithms
Lenka Zdeborová
Florent Krzakala
AI4CE
474
476
0
08 Nov 2015
Intensity-only optical compressive imaging using a multiply scattering
  material and a double phase retrieval approach
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach
Boshra Rajaei
Eric W. Tramel
S. Gigan
Florent Krzakala
L. Daudet
221
21
0
05 Oct 2015
1
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