I spent an hour this morning with Patel, discussing possible projects with the GALEX photon catalog. We tentatively decided to look for flashes or short-lived brightness increases, either on top of known sources or else in isolated regions. This project is interesting in itself, exercises the catalog, and also provides useful information for improving calibration and the instrument model.
At group meeting, Vakili showed a variant of a Gaussian Process, in which the latent function is still drawn from a Gaussian, but the data are related to the latent function by a fatter-tailed (t) distribution. He showed a beautiful simulation and output in which outliers totally mess up a Gaussian Process fit but are just straight-up ignored by the modified method. At this point, I don't even remember what the method is called, but it is extremely relevant to the quasar-fitting work by Mykytyn.
Arrrgh, don't start calling these 'non-Gaussian processes' like Ben Wandelt did in his IAUS306 talk! :-) [They are indeed still *latent* Gaussian processes within a hierarchical model (with an upper non-Gaussian layer) as your text below the title notes correctly.] We already have actual non-Gaussian processes: Gamma process, Dirichlet process, Poisson process, NB process etc.
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