Gaussian processes are lovely things. I’m a big fan. They are, however, thirsty. They will take your memory, your time, and anything else they can. Basically, the art of fitting Gaussian process models is the fine art of reducing the GP model until it’s simple enough to fit while still being flexible enough to be useful. There’s a long literature on effective approximation to Gaussian Processes that don’t turn out to be computational nightmares. I’m definitely not going to summarise...| Un garçon pas comme les autres (Bayes)
If you’re not a machine learner (and sometimes if you are), Gaussian processes need priors on their parameters. Like everything else to do with Gaussian processes, this can be delicate. This post works through some options.| Un garçon pas comme les autres (Bayes)