title: Varieties of Helmholtz Machine.
abstract: The Helmholtz machine is a new unsupervised learning architecture that uses top-down connections to build probability density models of input and bottom-up connections to build inverses to those models. The wake-sleep learning algorithm for the machine involves just the purely local delta rule. This paper suggests a number of different varieties of Helmholtz machines, each with its own strengths and weaknesses, and relates them to cortical information processing. Copyright 1996 Elsevier Science Ltd.
authors.affiliation: University of Toronto, USA
authors.forename: Geoffrey E.
authors.initials: GE
authors.lastname: Hinton
authors.forename: Peter
authors.initials: P
authors.lastname: Dayan