The Helmholtz machine is a type of artificial neural network that can account for the hidden structure of a set of data by being trained to create aâ€¦Â (More)

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2016

2016

Unsupervised training of deep generative models containing latent variables and performing inference remains a challengingâ€¦Â (More)

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2016

2016

- Haotian Xu, Zhijian Ou
- ArXiv
- 2016

Though with progress, model learning and performing posterior inference still remains a common challenge for using deepâ€¦Â (More)

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2015

2015

- Pavel Sountsov, Paul Miller
- Front. Comput. Neurosci.
- 2015

An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimalâ€¦Â (More)

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2010

2010

- Chi-Yung Yau, Kevin Burn, Stefan Wermter
- The 2010 International Joint Conference on Neuralâ€¦
- 2010

Emotional learning involves two stages. The first is to acquire reinforcers from stimuli and the second is to associate suchâ€¦Â (More)

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2003

2003

This paper addresses an algorithm for independent component analysis on the basis of Helmholtz machine, which is an unsupervisedâ€¦Â (More)

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2001

2001

We present an approach for text analysis, especially for topic words extraction and document classification, based on aâ€¦Â (More)

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2000

2000

- Byoung-Tak Zhang, Soo-Yong Shin
- PPSN
- 2000

A b s t r a c t . Recently, several evolutionary algorithms have been proposed that build and use an explicit distribution modelâ€¦Â (More)

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Review

1999

Review

1999

- Peter Dayan
- Neural Computation
- 1999

Many recent analysis-by-synthesis density estimation models of cortical learning and processing have made the crucial simplifyingâ€¦Â (More)

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Highly Cited

1996

Highly Cited

1996

- Peter Dayan, Geoffrey E. Hinton
- Neural Networks
- 1996

The Helmholtz machine is a new unsupervised learning architecture that uses top-down connections to build probability densityâ€¦Â (More)

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Highly Cited

1995

Highly Cited

1995

- Peter Dayan, Geoffrey E. Hinton, Radford M. Neal, Richard S. Zemel
- Neural Computation
- 1995

Discovering the structure inherent in a set of patterns is a fundamental aim of statistical inference or learning. One fruitfulâ€¦Â (More)

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