Bayesian methods for neural networks

Bishop, Christopher M. (1995). Bayesian methods for neural networks. Technical Report. Aston University, Birmingham.

Abstract

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
Published Date: 1995
Authors: Bishop, Christopher M.

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