Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

Dejan Pecevski; Lars Buesing; Wolfgang Maass

doi:10.1371/journal.pcbi.1002294

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Open Access

Peer-reviewed

Research Article

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

Dejan Pecevski ,

* E-mail: dejan@igi.tugraz.at

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria
⨯
Lars Buesing,

Current address: Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria
⨯
Wolfgang Maass

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria
⨯

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

Dejan Pecevski,
Lars Buesing,
Wolfgang Maass

Published: December 15, 2011
https://doi.org/10.1371/journal.pcbi.1002294

About the Authors

Dejan Pecevski

* E-mail: dejan@igi.tugraz.at

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria

Lars Buesing

Current address: Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria

Wolfgang Maass

Affiliation Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Conceived and designed the experiments: DP WM. Performed the experiments: DP. Analyzed the data: DP WM. Wrote the paper: DP WM. Contributed theory: DP LB WM.

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Neurons
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Neuronal dendrites
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Neural networks
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Action potentials
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Probability distribution
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Membrane potential
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Markov models
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Computer networks
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