Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey. (arXiv:2107.12521v2 [cs.LG] UPDATED)

This is a tutorial and survey paper on Boltzmann Machine (BM), Restricted
Boltzmann Machine (RBM), and Deep Belief Network (DBN). We start with the
required background on probabilistic graphical models, Markov random field,
Gibbs sampling, statistical physics, Ising model, and the Hopfield network.
Then, we introduce the structures of BM and RBM. The conditional distributions
of visible and hidden variables, Gibbs sampling in RBM for generating
variables, training BM and RBM by maximum likelihood estimation, and
contrastive divergence are explained. …

arxiv belief boltzmann lg machine network survey tutorial