An Application of Computable Distributions to the Semantics of Probabilistic Programs

TY - ICOMM

T1 - An Application of Computable Distributions to the Semantics of Probabilistic Programs

AU - Huang, Daniel

AU - Morrisett, Greg

AU - Spitters, Bas

N1 - Draft of a contribution to "Foundations of Probabilistic Programming"

PY - 2018/6/20

Y1 - 2018/6/20

N2 - In this chapter, we explore how (Type-2) computable distributions can be used to give both distributional and (algorithmic) sampling semantics to probabilistic programs with continuous distributions. Towards this end, we first sketch an encoding of computable distributions in a fragment of Haskell. Next, we show how topological domains can be used to model the resulting PCF-like language. Throughout, we hope to emphasize the connection of such an approach with ordinary programming.

AB - In this chapter, we explore how (Type-2) computable distributions can be used to give both distributional and (algorithmic) sampling semantics to probabilistic programs with continuous distributions. Towards this end, we first sketch an encoding of computable distributions in a fragment of Haskell. Next, we show how topological domains can be used to model the resulting PCF-like language. Throughout, we hope to emphasize the connection of such an approach with ordinary programming.

KW - cs.PL

M3 - Net publication - Internet publication

T3 - arXiv

PB - Cornell University

ER -