Church
Church: A language for generative models. We introduce Church, a universal language for describing stochastic generative processes. Church is based on the Lisp model of lambda calculus, containing a pure Lisp as its deterministic subset. The semantics of Church is defined in terms of evaluation histories and conditional distributions on such histories. Church also includes a novel language construct, the stochastic memoizer, which enables simple description of many complex non-parametric models. We illustrate language features through several examples, including: a generalized Bayes net in which parameters cluster over trials, infinite PCFGs, planning by inference, and various non-parametric clustering models. Finally, we show how to implement query on any Church program, exactly and approximately, using Monte Carlo techniques.
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References in zbMATH (referenced in 16 articles )
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- Hutter, Marcus; Lloyd, John W.; Ng, Kee Siong; Uther, William T.B.: Probabilities on sentences in an expressive logic (2013)
- Freer, Cameron E.; Roy, Daniel M.: Computable de Finetti measures (2012)
- Gutmann, Bernd; Thon, Ingo; Kimmig, Angelika; Bruynooghe, Maurice; De Raedt, Luc: The magic of logical inference in probabilistic programming (2011)
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