Hello, PyMC community!
I recently started discovering Gaussian Processes, but feel that those can be very powerful tools for modelling.
Can you please help me understand the difference between Latent and Marginal processes?
From PyMC docs I can only understand that Marginal has additive noise (while Latent does not).
Therefore:

Can you please say if there’s any difference for using Marginal and Latent processes on interpretation level? (i.e. for modelling which cases is best to choose which?)

I can as well see that there are some differences on how Marginal and Latent are implemented technically, e.g.:
 you cannot use Periodic covariance function with Latent processes (only Marginal)
 you can add some Latent process into your
pm.Deterministic
, while it seems to be impossible for Marginal  Marginal process requires some very specific
gp.marginal_likelihood
Are those peculiarities related to some conceptual difference of the processes or are purely technical?
Very much appreciate your recommendations!