Nicholas Hay

Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms

Despite the recent successes of probabilistic programming languages (PPLs) in AI applications, PPLs offer only limited support for random variables whose distributions combine discrete and continuous elements. We develop the notion of measure-theoretic Bayesian networks (MTBNs) and use it to provide…