This tutorial is meant to be an introduction to the principles of randomized and bayesian higher-order programming languages. We will start by giving some simple examples of probabilistic higher-order programs, written in generic or domain specific functional programming languages. Particular attention will be given in highlighting why sampling and conditioning can be useful in programming, and how the metatheory of higher-order probabilistic programming differs from the one of its deterministic sibling.
Mon 14 Jan Times are displayed in time zone: Greenwich Mean Time : Belfast change
|14:00 - 15:30|
|[T7] Higher-Order Probabilistic Programming|
Ugo Dal LagoUniversity of Bologna, Italy / Inria, FrancePre-print