Robust Full Bayesian Learning for Radial Basis Networks

DOI10.1162/089976601750541831zbMath1013.68179DBLPjournals/neco/AndrieuFD01OpenAlexW2122146783WikidataQ51642576 ScholiaQ51642576MaRDI QIDQ2762431

Arnaud Doucet, Christophe Andrieu, Nando de Freitas

Publication date: 28 February 2002

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

Full work available at URL: https://doi.org/10.1162/089976601750541831

zbMATH Keywords

neural networksBayesian modelradial basis networksMCMC simulated annealing algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

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Cites Work

• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Nonparametric regression using Bayesian variable selection
• Estimating the dimension of a model
• Neural networks: A review from a statistical perspective. With comments and a rejoinder by the authors
• Markov chains for exploring posterior distributions. (With discussion)
• A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• A new look at the statistical model identification

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