Your search
PROGRAMMING LANGUAGES
Publication year
Results
26 resources-
Wilkinson, D. (2019). A compositional approach to scalable Bayesian computation and probabilistic programming.
-
Borgström, J., Lago, U. D., Gordon, A. D., & Szymczak, M. (2017). A Lambda-Calculus Foundation for Universal Probabilistic Programming. ArXiv:1512.08990 [Cs]. Retrieved from http://arxiv.org/abs/1512.08990
-
Hur, C.-K., Nori, A. V., & Rajamani, S. K. (2015). A Provably Correct Sampler for Probabilistic Programs, 21.
-
Borchert, T. (2019). amzn/milan. Amazon. Retrieved from https://github.com/amzn/milan (Original work published 2019)
-
Staton, S. (2017). Commutative Semantics for Probabilistic Programming. In H. Yang (Ed.), Programming Languages and Systems (Vol. 10201, pp. 855–879). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-54434-1_32
-
Paquet, H., & Winskel, G. (2018). Continuous Probability Distributions in Concurrent Games. Electronic Notes in Theoretical Computer Science, 341, 321–344. https://doi.org/10/ggdmwv
-
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
-
Ehrhard, T. (2019). Differentials and distances in probabilistic coherence spaces. ArXiv:1902.04836 [Cs]. Retrieved from http://arxiv.org/abs/1902.04836
-
Law, J., & Wilkinson, D. (2019). Functional probabilistic programming for scalable Bayesian modelling. ArXiv:1908.02062 [Stat]. Retrieved from http://arxiv.org/abs/1908.02062
-
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
-
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
-
Keimel, K., & Plotkin, G. D. (2017). Mixed powerdomains for probability and nondeterminism. ArXiv:1612.01005 [Cs]. https://doi.org/10/ggdmrp
-
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
-
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 SIGPLAN-SIGACT Symposium on Principles of Programming Languages - POPL ’14 (pp. 309–320). San Diego, California, USA: ACM Press. https://doi.org/10/ggdf9x
-
Ehrhard, T., & Danos, V. (2011). Probabilistic coherence spaces as a model of higher-order probabilistic computation. Information and Computation, 209(6), 966–991. https://doi.org/10/ctfch6
-
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
-
Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452–459. https://doi.org/10/gdxwhq
-
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
-
Tix, R., Keimel, K., & Plotkin, G. (2009). Semantic Domains for Combining Probability and Non-Determinism. Electronic Notes in Theoretical Computer Science, 222, 3–99. https://doi.org/10/d9hwq7
Explore
BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
- Biology (1)
CATEGORICAL LOGIC
- Linear logic (6)
DIFFERENTIAL CALCULUS
- Differentiation (2)
MACHINE LEARNING
- Machine Learning (3)
MODEL CHECKING AND STATE MACHINES
- Rewriting theory (2)
- Transition systems (2)
PROBABILITY & STATISTICS
- Bayesian inference (13)
PROGRAMMING LANGUAGES
Methodology
- Implementation (10)
Topic
- Automatic differentiation (1)
- Bayesian inference (11)
- Bayesianism (2)
- Biology (1)
- Classical ML (1)
- Coherence spaces (4)
- Denotational semantics (10)
- Differential Linear Logic (1)
- Differentiation (2)
- Game semantics (3)
- Implementation (10)
- Interactive semantics (3)
- Linear logic (3)
- Machine learning (3)
- Powerdomains (2)
- Probabilistic programming
- Programming language theory (20)
- Rewriting theory (2)
- Semantics (4)
- Systems biology (1)
- Transition systems (2)
Resource type
- Blog Post (1)
- Book (1)
- Book Section (1)
- Computer Program (1)
- Conference Paper (6)
- Journal Article (15)
- Presentation (1)