Neuronal integration of dynamic sources: Bayesian learning and Bayesian inference

DOI10.1063/1.3491237zbMath1311.92052OpenAlexW2130773488WikidataQ45406739 ScholiaQ45406739MaRDI QIDQ5251242

Hava T. Siegelmann, Lars E. Holzman

Publication date: 19 May 2015

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://works.bepress.com/cgi/viewcontent.cgi?article=1007&context=hava_siegelmann

zbMATH Keywords

Bayesian learningsensory data

Mathematics Subject Classification ID

Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05) Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Cites Work

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• Belief Propagation in Networks of Spiking Neurons
• Memorization and Association on a Realistic Neural Model
• Efficient Computation Based on Stochastic Spikes

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