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Cited by 220

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Generative models for discovering sparse distributed representations

Open access
Hinton, Geoffrey E., Ghahramani, Zoubin·1997·Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences

Abstract

We describe a hierarchical, generative model that can be viewed as a nonlinear generalization of factor analysis and can be implemented in a neural network. The model uses bottom–up, top–down and lateral connections to perform Bayesian perceptual inference correctly. Once perceptual inference has been performed the connection strengths can be updated using a very simple learning rule that only requires locally available information. We demonstrate that the network learns to extract sparse, distributed, hierarchical representations.

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Crossref · 10.1098/rstb.1997.0101

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Metadata

Authors
Hinton, G. E., & Ghahramani, Z.
Venue
Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences
Published
1997-08-29
Volume
352
Issue
1358
Pages
1177-1190
ISSN
  • 0962-8436 (ISSN-L)
  • 1471-2970
OpenAlex
W1981814724
Cited by
220
References
3
FWCI
17.59
Type
journal article
Language
en
Open access
green

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