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Abramsky, S., Haghverdi, E., & Scott, P. (2002). Geometry of Interaction and Linear Combinatory Algebras. Mathematical. Structures in Comp. Sci., 12(5), 625–665. https://doi.org/10/fcsmhm

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

Borchert, T. (2019). amzn/milan. Amazon. Retrieved from https://github.com/amzn/milan (Original work published 2019)

Borgström, J., Lago, U. D., Gordon, A. D., & Szymczak, M. (2017). A LambdaCalculus Foundation for Universal Probabilistic Programming. ArXiv:1512.08990 [Cs]. Retrieved from http://arxiv.org/abs/1512.08990

Boutillier, P., Feret, J., Krivine, J., & Fontana, W. (n.d.). The Kappa Language and Kappa Tools, 52.

Boutillier, P., Maasha, M., Li, X., MedinaAbarca, H. F., Krivine, J., Feret, J., … Fontana, W. (2018). The Kappa platform for rulebased modeling. Bioinformatics, 34(13), i583–i592. https://doi.org/10/gdrhw6

Castellan, S., Clairambault, P., Paquet, H., & Winskel, G. (2018). The concurrent game semantics of Probabilistic PCF. In Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science  LICS ’18 (pp. 215–224). Oxford, United Kingdom: ACM Press. https://doi.org/10/ggdjfz

Dal Lago, U., & Hoshino, N. (2019). The Geometry of Bayesian Programming (pp. 1–13). https://doi.org/10/ggdk85

Danos, V., & Harmer, R. (2000). Probabilistic game semantics (Vol. 3, pp. 204–213). Presented at the ACM Transactions on Computational Logic  TOCL. https://doi.org/10/b6k43s

de Vink, E. P., & Rutten, J. J. M. M. (1997). Bisimulation for probabilistic transition systems: A coalgebraic approach. In P. Degano, R. Gorrieri, & A. MarchettiSpaccamela (Eds.), Automata, Languages and Programming (pp. 460–470). Berlin, Heidelberg: Springer. https://doi.org/10/fcqzmk

Desharnais, J., Edalat, A., & Panangaden, P. (2002). Bisimulation for Labelled Markov Processes. Information and Computation, 179(2), 163–193. https://doi.org/10/fmp9vd

Ehrhard, T. (2016). An introduction to Differential Linear Logic: proofnets, models and antiderivatives. ArXiv:1606.01642 [Cs]. Retrieved from http://arxiv.org/abs/1606.01642

Ehrhard, T. (2019). Differentials and distances in probabilistic coherence spaces. ArXiv:1902.04836 [Cs]. Retrieved from http://arxiv.org/abs/1902.04836

Ehrhard, T., & Danos, V. (2011). Probabilistic coherence spaces as a model of higherorder probabilistic computation. Information and Computation, 209(6), 966–991. https://doi.org/10/ctfch6

Ehrhard, T., Pagani, M., & Tasson, C. (2017). Measurable Cones and Stable, Measurable Functions. Proceedings of the ACM on Programming Languages, 2(POPL), 1–28. https://doi.org/10/ggdjf8

Ehrhard, T., Pagani, M., & Tasson, C. (2011). The Computational Meaning of Probabilistic Coherence Spaces. In 2011 IEEE 26th Annual Symposium on Logic in Computer Science (pp. 87–96). Toronto, ON, Canada: IEEE. https://doi.org/10/cpv52n

Ehrhard, T., & Regnier, L. (2003). The differential lambdacalculus. Theoretical Computer Science, 309(1), 1–41. https://doi.org/10/bf3b8v

Ehrhard, T., & Tasson, C. (2018). Probabilistic call by push value. ArXiv:1607.04690 [Cs]. https://doi.org/10/ggdk8z

Ehrhard, T., Tasson, C., & Pagani, M. (2014). Probabilistic coherence spaces are fully abstract for probabilistic PCF. In Proceedings of the 41st ACM SIGPLANSIGACT Symposium on Principles of Programming Languages  POPL ’14 (pp. 309–320). San Diego, California, USA: ACM Press. https://doi.org/10/ggdf9x

Engeler, E. (1995). The Combinatory Programme. Birkhäuser Basel. https://doi.org/10.1007/9781461242680
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