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Gaussian process regression with multiple response variables
2015
Chemometrics and Intelligent Laboratory Systems
Gaussian process regression (GPR) is a Bayesian non-parametric technology that has gained extensive application in data-based modelling of various systems, including those of interest to chemometrics. However, most GPR implementations model only a single response variable, due to the difficulty in the formulation of covariance function for correlated multiple response variables, which describes not only the correlation between data points, but also the correlation between responses. In the
doi:10.1016/j.chemolab.2015.01.016
fatcat:dl6qwy4bzrelxfdfbfl5x5rvfa