Computing at Glasgow University
Paper ID: 7022
DCS Tech Report Number: TR-2003-144

Learning a Gaussian Process Model with Uncertain Inputs
Girard,A. Murray-Smith,R.

Publication Type: Tech Report (internal)
Appeared in: DCS Tech Report
Page Numbers : 10
Publisher: N/A
Year: 2003

Learning with uncertain inputs is well-known to be a difficult task. In order to achieve this analytically using a Gaussian Process prior model, we expand the original process around the input mean (Delta method), assuming the random input is normally distributed. We thus derive a new process whose covariance function accounts for the randomness of the input. We illustrate the effectiveness of the proposed model on a simple static simulation example and on the modelling of a nonlinear noisy time-series.

Keywords: Gaussian Process, learning, random inputs

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