Approximate algorithms for neural-Bayesian approaches.

DOI10.1016/S0304-3975(02)00132-9zbMath1061.68127OpenAlexW2162191125MaRDI QIDQ1853467

Tom Heskes, Bert Kappen, Bart Bakker

Publication date: 21 January 2003

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-3975(02)00132-9

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• BayesDA

Cites Work

• A Bayesian/information theoretic model of learning to learn via multiple task sampling
• Testing precise hypotheses. With comments and a rejoinder by the authors
• Bayesian learning for neural networks
• Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks
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