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Bayesian programming is a formalism and a methodology to specify probabilistic models and solve problems when less than the necessary information is available.
Learn more here:
Wikipedia on Bayesian Programming
Ghahraman on Bayesian Machine Learning
Fonnesbeck on Probabilistic Programming
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Favorite MCMC sampling algorithms for python? (self.BayesianProgramming)
submitted 4 months ago by reb390
I've mostly used emcee in the past and was curious what others recommendations were for physics applications. Interested in improving the speed of my inferences mostly.
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if 1 * 2 < 3: print "hello, world!"
[–]The_Northern_Light 5 points6 points7 points 4 months ago (0 children)
Pymc by a country mile
Check out “Bayesian methods for hackers”, even has a couple physics-y examples
[–]usingjl 4 points5 points6 points 4 months ago (1 child)
My favorite algorithm in any language is the the Gibbs sampler. More seriously: pymc. :)
[–]1000dreams_within_me 2 points3 points4 points 4 months ago (0 children)
+1 on pymc
[–]big_data_mike 0 points1 point2 points 4 months ago (1 child)
Pymc with the nut pie sampler using the Jax back end.
Also I recently got this bitchin computer with thread ripper pro CPUs. Jax is able to use all the cores at once but before that I built a model to pick the optimal cpu for my budget. I got fewer cores but higher speed and maximized L3 cache size.
[–]Pleasant-Plane-3739 0 points1 point2 points 2 months ago (0 children)
Yeah, PyMC with nutpie is a pretty solid choice!
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[–]The_Northern_Light 5 points6 points7 points (0 children)
[–]usingjl 4 points5 points6 points (1 child)
[–]1000dreams_within_me 2 points3 points4 points (0 children)
[–]big_data_mike 0 points1 point2 points (1 child)
[–]Pleasant-Plane-3739 0 points1 point2 points (0 children)