Probabilistic Programming Language: Difference between revisions
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A Probabilistic Programming Language is a Programming Language that ...
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A [[Probabilistic Programming Language]] is a [[programming language]] that can naturally describe and infer with [[probabilistic model]]s. | |||
A [[Probabilistic Programming Language]] is a [[ | * <B>AKA:</B> [[PPL]]. | ||
* <B> | * <B>Counter-Example(s):</B> | ||
** a [[Deterministic Programming Language]]. | |||
* <B>See:</B> [[Stochastic Lambda Calculus]], [[Probabilistic Model]], [[Stan (Software)]]. | |||
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Revision as of 19:14, 21 September 2014
A Probabilistic Programming Language is a programming language that can naturally describe and infer with probabilistic models.
- AKA: PPL.
- Counter-Example(s):
- See: Stochastic Lambda Calculus, Probabilistic Model, Stan (Software).
References
2014
- (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/probabilistic_programming_language Retrieved:2014-9-21.
- A probabilistic programming language (PPL) is a programming language specially designed to describe and infer with probabilistic models.
PPLs often extend from a basic language. The inventors' choices of underlying basic language depend on the similarity of their models to the basic language's ontology, as well as commercial considerations and personal preference. For instance, Dimple[1] and Chimple[2] are based on Java, Infer.NET is based on .NET framework,[3] while PRISM extends from Prolog.[4] However, some PPLs such as WinBUGS and Stan (software) define a self-contained language for their users to use, which is not obviously derived from a predecessor language.[5][6]
Currently there are several PPLs in active development, some of them have advanced to the beta stage. However because PRMs are new, up to year 2010 there have been no well-known software projects utilizing those languages.
- A probabilistic programming language (PPL) is a programming language specially designed to describe and infer with probabilistic models.
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