A Gaussian process is defined as a collection of random variables, any finite number of which have a joint Gaussian distribution.
While we often have ideas about the functions we want to model — whether they’re smooth, periodic, quickly varying, etc. — it is relatively tedious to reason about the parameters, which are largely uninterpretable
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