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

10 February 2017

Marylou Gabrié

Florent Krzakala

ArXiv (abs)PDF HTML

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

9 / 9 papers shown

Title
Unsupervised hierarchical clustering using the learning dynamics of RBMs A. Decelle Lorenzo Rosset Beatriz Seoane 79 5 0 03 Feb 2023
Restricted Boltzmann Machine, recent advances and mean-field theory A. Decelle Cyril Furtlehner AI4CE 64 55 0 23 Nov 2020
Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach Burak Çakmak Manfred Opper 39 4 0 14 Jan 2020
Mean-field inference methods for neural networks Marylou Gabrié AI4CE 120 33 0 03 Nov 2019
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins J. Tubiana Simona Cocco R. Monasson 48 28 0 18 Feb 2019
Memory-free dynamics for the TAP equations of Ising models with arbitrary rotation invariant ensembles of random coupling matrices Burak Çakmak Manfred Opper 75 20 0 24 Jan 2019
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 133 880 0 23 Mar 2018
Thermodynamics of Restricted Boltzmann Machines and related learning dynamics A. Decelle G. Fissore Cyril Furtlehner AI4CE 99 43 0 05 Mar 2018
Learned D-AMP: Principled Neural Network based Compressive Image Recovery Christopher A. Metzler Ali Mousavi Richard G. Baraniuk 91 286 0 21 Apr 2017