Hello, I modelled my 2-dimensional data (one being a continuous value and one being the category the datapoint stems from) with gaussian processes in 2 ways that should actually be equivalent but somehow I yield different prediction results (the posterior seems fine). The only difference is basical…

Maybe, I wouldn’t be surprised. Cloning a PyMC model is not trivial and I don’t expect deepcopy to do a good job. This is specially relevant for GPs, as they hold references to old variables in the instances. PyMC has a clone_model utility, but for similar reasons that won’t work properly with GP o…

Equivalent GP models, different results

Questions v5

bwengals October 16, 2023, 6:58pm 2

Hmm, nothing obvious jumps out. It does look like both should be equivalent. When are you calling pm.sample?

Maybe one prediction includes the likelihood noise and the other doesn’t?

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Equivalent GP models, different results

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