A Restricted Boltzmann Machine is a generative stochastic neural network that learns a probability distribution over input data. It has visible and hidden units with restricted connections, and has historically been used for representation learning, dimensionality reduction, and generative modeling.
A generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.