Bayesian Inference using the Symmetric Monoidal Closed Category Structure

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.

Corrected the pullback diagram. Comments/corrections are welcomed

References in corpus (1)

• Categorical Probability Theory

Cited by in corpus (1)

• The Giry Monad is not Strong for the Canonical Symmetric Monoidal Closed Structure on Meas