” Following Helmholtz, we view the human perceptual system as a statistical inference engine whose function is to infer the probable causes of sensory input. We show that a device of this kind can learn how to perform these inferences without requiring a teacher to label each sensory input vector with its underlying causes. A recognition model is used to infer a probability distribution over the underlying causes from the sensory input, and a separate generative model, which is also learned, is used to train the recognition model.

[…]

The Helmholtz machine fits comfortably within the framework of Grenander’s pattern theory (Grenander 1976) in the
form of Mumford’s (1994) proposals for the mapping onto the brain.”