@inbook{f9e1e8259d4d4d5dae6904b0e1b0e262,
title = "Bayesian methods for neural networks",
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.",
keywords = "bayesian, neural networks, learning, pattern recognition",
author = "Bishop, {Christopher M.}",
year = "1995",
language = "English",
editor = "L. Tarassenko and E. Rolls and D. Sherrington",
booktitle = "Oxford Lectures on Neural Networks",
publisher = "Oxford University Press",
address = "United Kingdom",
}