Bayesian Inference using the Symmetric Monoidal Closed Category Structure
Category Theory
2016-02-05 v3 Probability
Abstract
Using the symmetric monoidal closed category structure of the category of measurable spaces, in conjunction with the Giry monad which we show is a strong monad, we analyze Bayesian inference maps and their construction in relation to the tensor product probability. This perspective permits the inference maps to be seen as a pullback construction.
Cite
@article{arxiv.1601.02593,
title = {Bayesian Inference using the Symmetric Monoidal Closed Category Structure},
author = {Kirk Sturtz},
journal= {arXiv preprint arXiv:1601.02593},
year = {2016}
}
Comments
Corrected the pullback diagram. Comments/corrections are welcomed