(2nd-Dec-2020)
• A deep Boltzmann machine or DBM (Salakhutdinov and Hinton 2009a , ) is another kind of deep, generative model. Unlike the deep belief network (DBN), it is an entirely undirected model. Unlike the RBM, the DBM has several layers of latent variables (RBMs have just one). But like the RBM, within each layer, each of the variables are mutually independent, conditioned on the variables in the neighboring layers. See figure for the graph structure. Deep Boltzmann 20.2 machines have been applied to a variety of tasks including document modeling (Srivastava 2013 et al., ). Like RBMs and DBNs, DBMs typically contain only binary units—as we assume for simplicity of our presentation of the model—but it is straightforward to include real-valued visible units.
• A deep Boltzmann machine, re-arranged to revealits bipartite graph structure
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