Stochastic Probabilistic Programs
This addresses a technical bottleneck in probabilistic programming for researchers and practitioners working with complex statistical models.
The paper introduces stochastic probabilistic programs to simplify specification and improve inference efficiency for models with nuisance parameters, noise, and nondeterminism, demonstrating this through examples and comparisons with deterministic probabilistic programs.
We introduce the notion of a stochastic probabilistic program and present a reference implementation of a probabilistic programming facility supporting specification of stochastic probabilistic programs and inference in them. Stochastic probabilistic programs allow straightforward specification and efficient inference in models with nuisance parameters, noise, and nondeterminism. We give several examples of stochastic probabilistic programs, and compare the programs with corresponding deterministic probabilistic programs in terms of model specification and inference. We conclude with discussion of open research topics and related work.