In programming languages and machine learning, Bayesian program synthesis (BPS) is a program synthesis technique where Bayesian probabilistic programs automatically construct new Bayesian probabilistic programs.[1] This approach stands in contrast to routine practice in probabilistic programming where human developers manually write new probabilistic programs.
- ^ Saad, Feras A.; Cusumano-Towner, Marco F.; Schaechtle, Ulrich; Rinard, Martin C.; Mansinghka, Vikash K. (January 2019). "Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling". Proc. ACM Program. Lang. 3 (POPL): 37:1–37:32. arXiv:1907.06249. Bibcode:2019arXiv190706249S. doi:10.1145/3290350. ISSN 2475-1421. S2CID 53697125.
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