3 citations · 4 across the 6 of their papers we have counts for
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cs.PL2023★ 3 cited
Probabilistic programming interfaces for random graphs: Markov categories, graphons, and nominal sets
Nathanael L. Ackerman, Cameron E. Freer, Younesse Kaddar +5
We study semantic models of probabilistic programming languages over graphs, and establish a connection to graphons from graph theory and combinatorics. We show that every well-beh…
cs.PL2023★ 1 cited
A model of stochastic memoization and name generation in probabilistic programming: categorical semantics via monads on presheaf categories
Younesse Kaddar, Sam Staton
Stochastic memoization is a higher-order construct of probabilistic programming languages that is key in Bayesian nonparametrics, a modular approach that allows us to extend models…