Contextual Equivalence for a Probabilistic Language with Continuous Random Variables

Abstract

We present a complete reasoning principle for contextual equivalence in an untyped probabilistic programming language. The language includes continuous random variables, conditionals, and scoring. The language also includes recursion, since in an untyped language the standard call-by-value fixpoint combinator is expressible. The language is similar to that… (More)

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