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Jones, C., & Plotkin, G. (1989). A Probabilistic Powerdomain of Evaluations. In Proceedings of the Fourth Annual Symposium on Logic in Computer Science (pp. 186–195). Piscataway, NJ, USA: IEEE Press. Retrieved from http://dl.acm.org/citation.cfm?id=77350.77370
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Healy, M. J. (2000). Category theory applied to neural modeling and graphical representations. In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium (pp. 35–40 vol.3). Como, Italy: IEEE. https://doi.org/10/dr29pc
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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
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Ehrhard, T., Tasson, C., & Pagani, M. (2014). Probabilistic coherence spaces are fully abstract for probabilistic PCF. In Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages - POPL ’14 (pp. 309–320). San Diego, California, USA: ACM Press. https://doi.org/10/ggdf9x
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Ścibior, A., Ghahramani, Z., & Gordon, A. D. (2015). Practical Probabilistic Programming with Monads. In Proceedings of the 2015 ACM SIGPLAN Symposium on Haskell (pp. 165–176). New York, NY, USA: ACM. https://doi.org/10/gft39z
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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
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Sprunger, D., & Katsumata, S. (2019). Differentiable Causal Computations via Delayed Trace. In 2019 34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) (pp. 1–12). Vancouver, BC, Canada: IEEE. https://doi.org/10/ggdf98
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