A restricted Boltzmann machine (RBM), originally invented under the name harmonium, is a popular building block for deep probabilistic models. For example, they are the constituents of deep belief networks that started the recent surge in deep learning advances in 2006.
RBMs specify joint probability distributions over random variables, both visible and latent, using an energy function, similar to Boltzmann machines, but with some restrictions. Hence the name. In this article, we will introduce Boltzmann machines and their extension to RBMs.