@techreport{bishop1995bayesian,
author = {Bishop, Christopher},
title = {Bayesian methods for neural networks},
year = {1995},
month = {January},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/bayesian-methods-for-neural-networks/},
edition = {Technical Report NCRG/95/009, Neural Computing Research Group, Aston University},
number = {NCRG/95/009},
note = {USENIX ICAC},
}