Designing neural networks that process mean values of random variables

DOI10.1016/J.PHYSLETA.2014.04.065zbMath1331.92014arXiv1004.5326OpenAlexW2169491055MaRDI QIDQ5964310

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Publication date: 29 February 2016

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1004.5326

zbMATH Keywords

Bayesian networksneural networksBayesian inferenceneural information processingpopulation codingprobabilistic models

Mathematics Subject Classification ID

Bayesian inference (62F15) Neural networks for/in biological studies, artificial life and related topics (92B20) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (1)

ZFD formula \(4\mathrm{I}g\mathrm{SFD}\_\mathrm{Y}\) applied to future minimization

Cites Work

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• Connectionist learning of belief networks
• Developing and applying a toolkit from a general neurocomputational framework
• Probabilistic Independence Networks for Hidden Markov Probability Models
• Population Coding and Decoding in a Neural Field: A Computational Study
• Neural Representation of Probabilistic Information

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