= Probabilistic programming
<Probabilistic programming> expresses a <probability model> as an executable program with random choices and observations. Executing the generative part induces a <probability distribution>; observations then restrict or weight executions, and inference computes the resulting <conditional distribution>. Program syntax and inference algorithm are separate choices: the same model can be evaluated by <rejection sampling>, <importance sampling> or <Markov chain Monte Carlo>.
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