Issues in Bayesian Analysis of Neural Network Models
Keyword(s):
Stemming from work by Buntine and Weigend (1991) and MacKay (1992), there is a growing interest in Bayesian analysis of neural network models. Although conceptually simple, this problem is computationally involved. We suggest a very efficient Markov chain Monte Carlo scheme for inference and prediction with fixed-architecture feedforward neural networks. The scheme is then extended to the variable architecture case, providing a data-driven procedure to identify sensible architectures.
2020 ◽
2020 ◽
2005 ◽
Vol 15
(05)
◽
pp. 323-338
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2020 ◽
2018 ◽
Vol 6
(11)
◽
pp. 216-216
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Keyword(s):
Keyword(s):
Keyword(s):