Markov category
Markov categories are copy-discard categories of total morphisms that have conditionals. From conditionals, we can prove the existence of Bayesian inversions. The main example is the category of distributions ( Stoch, the Kleisli category of the finitary distribution monad); continuous examples are given by standard Borel spaces (see Giry monad) and normal Gaussian noise (see Gaussian probability theory).
- conditional
- partial Markov category
- discrete partial Markov category
- First action of produoidal Markov split
- Second action of produoidal Markov split
- distributions that are marginally independent of the parameter
- divergence on a Markov category
Tags: probability, monoidal category.
References.