Regression with Gaussian processes

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract / Description of output

The Bayesian analysis of neural networks is difficult because the prior over functions has a complex form, leading to implementations that either make approximations or use Monte Carlo integration techniques. In this paper I investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis to be carried out exactly using matrix operations. The method has been tested on two challenging problems and has produced excellent results.
Original languageEnglish
Title of host publicationMathematics of Neural Networks
Subtitle of host publicationModels, Algorithms and Applications
PublisherSpringer US
Number of pages5
ISBN (Electronic)978-1-4615-6099-9
ISBN (Print)978-1-4613-7794-8
Publication statusPublished - 1995

Publication series

NameOperations Research/Computer Science Interfaces Series


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