A GP model of the objective function f (x) can be interpreted as (i, weight space view) Bayesian linear regression in the implicit feature space of the kernel and (ii, function space view) a distribution over functions [ ]. To clarify, the GP model of f (x) in eqn. is equivalent to the parametric model: