An application of computable distributions to the semantics of probabilistic programs
Our attempt to give semantics to a core, functional probabilistic programming language uses computable distributions. The semantics uses largely standard techniques from denotational semantics. One nice property of computable distributions is that they are completely characterized by a sampling algorithm. Hence, it is possible to faithfully implement (in a Turing-complete language) a semantics based on computable distributions as a sampling library.… Read the rest