Sparse Multi-output Gaussian Processes
Mauricio A. Álvarez, Neil David Lawrence · 2008
We consider the problem of modelling correlated outputs from a single Gaussian process (GP). Modelling multiple output variables is a challenge as we are required to compute cross covariances between the different outputs. These cross covariances allow us to improve our predictions of one output given the others as the correlations between outputs are modelled [1, 2, 3, 4].