Bayesian Neural Networks

Christopher M. Bishop

Research output: Contribution to journalArticlepeer-review


Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a solution to the problem of over-fitting. This article provides an introductory overview of the application of Bayesian methods to neural networks. It assumes the reader is familiar with standard feed-forward network models and how to train them using conventional techniques.
Original languageEnglish
Pages (from-to)61–68
Number of pages8
JournalJournal of the Brazilian Computer Society
Issue number1
Publication statusPublished - Jul 1997


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