We introduce a multilayer deep generative model capable of learning hierarchies of sparse distributed representations from data. The model consists of several layers of stochastic units, with autoregressive connections within each layer, which allows for efficient exact sampling. We train the model efficiently using an algorithm derived from the Minimum Desc