28 citations · 159 across the 26 of their papers we have counts for
4 papers · 1 filter
Markov Categories and Entropy
Paolo Perrone
Markov categories are a novel framework to describe and treat problems in probability and information theory. In this work we combine the categorical formalism with the traditional…
Dilations and information flow axioms in categorical probability
Tobias Fritz, Tomáš Gonda, Nicholas Gauguin Houghton-Larsen +3
We study the positivity and causality axioms for Markov categories as properties of dilations and information flow in Markov categories, and in variations thereof for arbitrary sem…
A category-theoretic proof of the ergodic decomposition theorem
Sean Moss, Paolo Perrone
The ergodic decomposition theorem is a cornerstone result of dynamical systems and ergodic theory. It states that every invariant measure on a dynamical system is a mixture of ergo…
Probability monads with submonads of deterministic states - Extended version
Sean Moss, Paolo Perrone
Probability theory can be studied synthetically as the computational effect embodied by a commutative monad. In the recently proposed Markov categories, one works with an abstracti…