Hi, I’m doing probabilistic regression, in this case, using Gaussian Process. After i followed the Marginal Likelihood using Gaussian Process tutorial Marginal Likelihood Implementation , i am questioning about to do inference. here is some example what i did in my code, with pm.Model() as model: …

Hi @mozzy , pm.find_MAP runs optimization which gives you exactly one parameter set (the maximum-a-posteriori estimate). If you’re lucky that’s the mode of the posterior distribution, but more often than not - and particularly in high dimensional spaces it’s not representative. pm.sample on the ot…

What makes difference find_MAP() and pm.sample()

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mozzy October 17, 2021, 3:42am 3

I see, thank you for the answer. Maybe i could different strategy to compute the hyperparameter.

Thanks!

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What makes difference find_MAP() and pm.sample()

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