Multi-task GPs can be used on multioutput functions 𝑓: χ → 𝑅 + , where each of the 𝑇 outputs can be seen as solutions to unique regression tasks. The key idea is to use a kernel that can extend to multiple tasks. As detailed in the work by Bonilla et al., we use the intrinsic model of coregionalization, which transforms a latent function to yield the outputs: