Bayesian methods for neural networks


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 potential solution to the problem of over-fitting. This chapter aims to provide 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.

Divisions: Aston University (General)
Uncontrolled Keywords: Bayesian,neural networks,learning,pattern recognitio
ISBN: NCRG/95/009
Last Modified: 27 Dec 2023 10:14
Date Deposited: 09 Jul 2009 09:52
PURE Output Type: Technical report
Published Date: 1995
Authors: Bishop, Christopher M.


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