1 citations · 2 across the 4 of their papers we have counts for
4 papers
Compositional Inference for Bayesian Networks and Causality
Bart Jacobs, Márk Széles, Dario Stein
Inference is a fundamental reasoning technique in probability theory. When applied to a large joint distribution, it involves updating with evidence (conditioning) in one or more c…
Combs, Causality and Contractions in Atomic Markov Categories
Dario Stein, Márk Széles
We present a counterexample showing that Markov categories with conditionals (such as BorelStoch) need not validate a natural scheme of axioms which we call contraction identities.…
Overdrawing Urns using Categories of Signed Probabilities
Bart Jacobs, Dario Stein
A basic experiment in probability theory is drawing without replacement from an urn filled with multiple balls of different colours. Clearly, it is physically impossible to overdra…
Pearl's and Jeffrey's Update as Modes of Learning in Probabilistic Programming
Bart Jacobs, Dario Stein
The concept of updating a probability distribution in the light of new evidence lies at the heart of statistics and machine learning. Pearl's and Jeffrey's rule are two natural upd…