Bayesian representation learning in the cortex regulated by acetylcholine

DOI10.1016/j.neunet.2004.06.006zbMath1056.92011OpenAlexW2081226981WikidataQ45149451 ScholiaQ45149451MaRDI QIDQ705585

Junichiro Yoshimoto, Shin Ishii, Jun-ichiro Hirayama

Publication date: 31 January 2005

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2004.06.006

zbMATH Keywords

Model selectionOn-line learningAcetylcholineCortical representationProbabilistic principal component analysisVariational Bayes method

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) 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)

Related Items (1)

Superresolution with compound Markov random fields via the variational EM algorithm

Cites Work

• Online Model Selection Based on the Variational Bayes
• Probabilistic Principal Component Analysis
• Sequential Bayesian Decoding with a Population of Neurons

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