Varieties of Helmholtz Machine

نویسندگان

  • Peter Dayan
  • Geoffrey E. Hinton
چکیده

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.

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................................................................................V DECLARATION OF ORIGINALITY ........................................... VII ACKNOWLEDGEMENTS........................................................... IX TABLE OF CONTENTS.............................................................. XI TABLE OF FIGURES.................................................................

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عنوان ژورنال:
  • Neural networks : the official journal of the International Neural Network Society

دوره 9 8  شماره 

صفحات  -

تاریخ انتشار 1996