De Finetti's Theorem in Categorical Probability

05/06/2021
by   Tobias Fritz, et al.
0

We present a novel proof of de Finetti's Theorem characterizing permutation-invariant probability measures of infinite sequences of variables, so-called exchangeable measures. The proof is phrased in the language of Markov categories, which provide an abstract categorical framework for probability and information flow. The diagrammatic and abstract nature of the arguments makes the proof intuitive and easy to follow. We also show how the usual measure-theoretic version of de Finetti's Theorem for standard Borel spaces is an instance of this result.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/14/2020

Representable Markov Categories and Comparison of Statistical Experiments in Categorical Probability

Markov categories are a recent categorical approach to the mathematical ...
research
07/12/2022

The d-separation criterion in Categorical Probability

The d-separation criterion detects the compatibility of a joint probabil...
research
07/15/2022

A category-theoretic proof of the ergodic decomposition theorem

The ergodic decomposition theorem is a cornerstone result of dynamical s...
research
08/01/2023

Absolute continuity, supports and idempotent splitting in categorical probability

Markov categories have recently turned out to be a powerful high-level f...
research
12/09/2022

The unstable formula theorem revisited

We first prove that Littlestone classes, those which model theorists cal...
research
10/05/2018

Corrections to "Wyner's Common Information under Rényi Divergence Measures"

In this correspondence, we correct an erroneous argument in the proof of...
research
09/07/2018

The Force of Proof by Which Any Argument Prevails

Jakob Bernoulli, working in the late 17th century, identified a gap in c...

Please sign up or login with your details

Forgot password? Click here to reset