ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1702.03260
  4. Cited By
A Deterministic and Generalized Framework for Unsupervised Learning with
  Restricted Boltzmann Machines
v1v2v3 (latest)

A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines

Physical Review X (PRX), 2017
10 February 2017
Eric W. Tramel
Marylou Gabrié
Andre Manoel
F. Caltagirone
Florent Krzakala
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines"

16 / 16 papers shown
Inferring effective couplings with Restricted Boltzmann Machines
Inferring effective couplings with Restricted Boltzmann MachinesSciPost Physics (SciPost Phys.), 2023
A. Decelle
Cyril Furtlehner
Alfonso De Jesus Navas Gómez
Beatriz Seoane
AI4CE
442
14
0
05 Sep 2023
Fast and Functional Structured Data Generators Rooted in
  Out-of-Equilibrium Physics
Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium PhysicsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
A. Carbone
A. Decelle
Lorenzo Rosset
Beatriz Seoane
SyDa
318
9
0
13 Jul 2023
Unsupervised hierarchical clustering using the learning dynamics of RBMs
Unsupervised hierarchical clustering using the learning dynamics of RBMsPhysical Review E (PRE), 2023
A. Decelle
Lorenzo Rosset
Beatriz Seoane
331
7
0
03 Feb 2023
JSRNN: Joint Sampling and Reconstruction Neural Networks for High
  Quality Image Compressed Sensing
JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing
Chunyan Zeng
Jiaxiang Ye
Zhifeng Wang
Nan Zhao
Minghu Wu
AI4TS
157
2
0
11 Nov 2022
Privacy-preserving machine learning with tensor networks
Privacy-preserving machine learning with tensor networksQuantum (Quantum), 2022
Alejandro Pozas-Kerstjens
Senaida Hernández Santana
José Ramón Pareja Monturiol
Marco Castrillón López
G. Scarpa
Carlos E. González-Guillén
David Pérez-García
266
7
0
24 Feb 2022
Restricted Boltzmann Machine, recent advances and mean-field theory
Restricted Boltzmann Machine, recent advances and mean-field theoryChinese Physics B (Chin. Phys. B), 2020
A. Decelle
Cyril Furtlehner
AI4CE
404
66
0
23 Nov 2020
A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann
  Machines
A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann MachinesJournal of Statistical Mechanics: Theory and Experiment (JSTAT), 2020
Burak Çakmak
Manfred Opper
AI4CE
185
12
0
04 May 2020
Analysis of Bayesian Inference Algorithms by the Dynamical Functional
  Approach
Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach
Burak Çakmak
Manfred Opper
152
4
0
14 Jan 2020
Mean-field inference methods for neural networks
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
421
37
0
03 Nov 2019
Learning Compositional Representations of Interacting Systems with
  Restricted Boltzmann Machines: Comparative Study of Lattice Proteins
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins
J. Tubiana
Simona Cocco
R. Monasson
162
29
0
18 Feb 2019
Memory-free dynamics for the TAP equations of Ising models with
  arbitrary rotation invariant ensembles of random coupling matrices
Memory-free dynamics for the TAP equations of Ising models with arbitrary rotation invariant ensembles of random coupling matrices
Burak Çakmak
Manfred Opper
185
20
0
24 Jan 2019
A Simple Algorithm for Scalable Monte Carlo Inference
A Simple Algorithm for Scalable Monte Carlo Inference
A. Borisenko
M. Byshkin
Alessandro Lomi
251
10
0
02 Jan 2019
Incorporating Scalability in Unsupervised Spatio-Temporal Feature
  Learning
Incorporating Scalability in Unsupervised Spatio-Temporal Feature Learning
S. Paul
Sourya Roy
Amit K. Roy-Chowdhury
SSL
188
1
0
06 Aug 2018
A high-bias, low-variance introduction to Machine Learning for
  physicists
A high-bias, low-variance introduction to Machine Learning for physicists
Pankaj Mehta
Marin Bukov
Ching-Hao Wang
A. G. Day
C. Richardson
Charles K. Fisher
D. Schwab
AI4CE
450
975
0
23 Mar 2018
Thermodynamics of Restricted Boltzmann Machines and related learning
  dynamics
Thermodynamics of Restricted Boltzmann Machines and related learning dynamics
A. Decelle
G. Fissore
Cyril Furtlehner
AI4CE
346
49
0
05 Mar 2018
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
465
306
0
21 Apr 2017
1
Page 1 of 1