NUTS

Bayesian golf puttings, NUTS, and optimizing your sampling function with TensorFlow Probability

TL;DR We’ll: Port a great Bayesian modelling tutorial from Stan to TFP Discuss how to speed up our sampling function Use the trace_fn to produce Stan-like generated quantities Explore the results using the ArviZ library. Intro This is a TFP-port one of of the best Bayesian modelling tutorials I’ve seen online - the Model building and expansion for golf putting Stan tutorial. It’s a beautiful example of modeling from first principles, and why the incorporation of domain knowledge into a statistical model - in this case, knowing a little bit about golf and some high-school physics - is so important.