Hierarchical priors for Function learning

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It is common to learn also the parameters of the GaussianRandomField covariance kernel e.g. the lengthscales appearing within the Matern kernel.
Such parameters can often be jointly learnt with the parameter-learning problem, but this would require a suitable framework to sample from such distributions and build the GRF's internally.