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Restricted Boltzmann Machines (RBM) are bi-layer neural networks used for the unsupervised learning of model distributions from data. The bipartite architecture of RBM naturally defines an elegant sampling procedure, called Alternating Gibbs Sampling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0bc54e03b7bcd63c0e762ce74e4a634
