A Brief Introduction to Gaussian Processes

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at UCLA on Jul 27, 2012 [pdf]
Neil D. Lawrence, University of Sheffield

Abstract

Gaussian processes are non-parametric probabilistic models for function representation. In this tutorial we give a brief introduction to Gaussian process models. Using simple examples we show how, with particular choices for covariance functions (analagous to a kernel matrix in kernel methods), we can perform inference about functions using only data sampled from those functions. We give overview how the probabilistic interpretation allows us to fit the parameters of the covariance function.

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