Efficient Markov Chain Monte Carlo for Bayesian Analysis of Neural Network Models |
Paul E. Green
(Department of Statistics, Seoul National University)
Changha Hwang (Department of Statistics, Catholic University of Taegu) Lee, Sangbock (Department of Statistics, Catholic University) |
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Markov chain Monte Carlo methods based on 'slicing' the density function
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Feedforward neural networks for nonparametric regression
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Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
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DOI ScienceOn |
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Bayesian radial basis functions of variable dimension
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DOI ScienceOn |
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Model Selection and Model Averaging for Neural Networks
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Probable networks and plausible predictions- a review of practical Bayesian methods for supervised neural networks
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The structure and dynamics of ringed galaxies, III
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DOI |
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Bayesian methods for neural networks
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Issues in Bayesian analysis of neural network models
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DOI ScienceOn |
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Slice sampling
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