A domain theory for statistical probabilistic programming
<p>We give an adequate denotational semantics for languages with recursive higher-order types, continuous probability distributions, and soft constraints. These are expressive languages for building Bayesian models of the kinds used in computational statistics and machine learning. Among them...
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| Format: | Conference item |
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Association for Computing Machinery
2019
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