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Baudart, G., Mandel, L., Atkinson, E., Sherman, B., Pouzet, M., & Carbin, M. (2019). Reactive Probabilistic Programming. ArXiv:1908.07563 [Cs]. Retrieved from http://arxiv.org/abs/1908.07563
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Law, J., & Wilkinson, D. (2019). Functional probabilistic programming for scalable Bayesian modelling. ArXiv:1908.02062 [Stat]. Retrieved from http://arxiv.org/abs/1908.02062
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Vákár, M., Kammar, O., & Staton, S. (2018). A Domain Theory for Statistical Probabilistic Programming. ArXiv:1811.04196 [Cs]. Retrieved from http://arxiv.org/abs/1811.04196
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Ścibior, A., Kammar, O., & Ghahramani, Z. (2018). Functional programming for modular Bayesian inference. Proceedings of the ACM on Programming Languages, 2(ICFP), 1–29. https://doi.org/10/gft39x
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Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., … Ghahramani, Z. (2017). Denotational validation of higher-order Bayesian inference. Proceedings of the ACM on Programming Languages, 2(POPL), 1–29. https://doi.org/10.1145/3158148
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Tran, D., Hoffman, M. D., Saurous, R. A., Brevdo, E., Murphy, K., & Blei, D. M. (2017). Deep Probabilistic Programming. ArXiv:1701.03757 [Cs, Stat]. Retrieved from http://arxiv.org/abs/1701.03757
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Jacobs, B., & Zanasi, F. (2017). A Formal Semantics of Influence in Bayesian Reasoning. Schloss Dagstuhl - Leibniz-Zentrum Fuer Informatik GmbH, Wadern/Saarbruecken, Germany. https://doi.org/10/ggdgbc
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Jacobs, B., & Zanasi, F. (2016). A Predicate/State Transformer Semantics for Bayesian Learning. Electronic Notes in Theoretical Computer Science, 325, 185–200. https://doi.org/10/ggdgbb
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Staton, S., Yang, H., Heunen, C., Kammar, O., & Wood, F. (2016). Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints. Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer Science - LICS ’16, 525–534. https://doi.org/10/ggdf97
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Hur, C.-K., Nori, A. V., & Rajamani, S. K. (2015). A Provably Correct Sampler for Probabilistic Programs, 21.
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Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452–459. https://doi.org/10/gdxwhq
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