A high-level programming language that more readily enables a developer to design probability models and then automatically “solve” these models. Probabilistic programming languages make it possible to reuse model libraries, interactive support modeling, and formal verification, and provide an abstraction layer necessary to foster generic, efficient inference in universal model classes.
Comparison of Probabilistic Programming and Random Variables
In this programming “random variables ” are used instead of simple variables and using probabilistic programming it is easy to develop generative story rather than a black box.
Probabilistic Programming Applications
Probabilistic programming languages can accommodate the uncertain and incomplete information that is so common in the business domain. We will see wider adoption of these languages and expect them also to be applied to deep learning.