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We investigate the thermodynamic properties of a Restricted Boltzmann Machine (RBM), a simple energy-based generative model used in the context of unsupervised learning.
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Training products of experts by minimizing contrastive divergence
G. E. Hinton · 2002
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Reducing the dimensionality of data with neural networks
G.E. Hinton and R.R. Salakhutdinov · 2006
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Training restricted Boltzmann machines using approximations to the likelihood gradient
T. Tieleman · 2008
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Deep Boltzmann machines
R. Salakhutdinov and G. Hinton · 2009
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Training restricted Boltzmann machines via the Thouless-Anderson-Palmer free energy
G. Marylou, E.W. Tramel, and F. Krzakala · 2015
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Advanced mean-field theory of the restricted Boltzmann machine
H. Huang and T. Toyoizumi · 2015
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Mean-field inference in gaussian restricted Boltzmann machine
C. Takahashi and M. Yasuda · 2016
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Statistical physics of inference: thresholds and algorithms
L. Zdeborová and F. Krzakala · 2016
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Nonequilibrium thermodynamics of restricted Boltzmann machines
D.S.P. Salazar · 2017
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A Practical Guide to Training Restricted Boltzmann Machines
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On the equivalence of Hopfield networks and Boltzmann machines
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Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses
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Emergence of compositional representations in restricted Boltzmann machines
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Spectral dynamics of learning in restricted Boltzmann machines
A. Decelle, G. Fissore, and C. Furtlehner · 2017
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