Your search
PROGRAMMING LANGUAGES
Results
38 resources
Murfet, D. (2019). dmurfet/2simplicialtransformer. Retrieved from https://github.com/dmurfet/2simplicialtransformer (Original work published 2019)

Murfet, D., Clift, J., Doryn, D., & Wallbridge, J. (2019). Logic and the $2$Simplicial Transformer. ArXiv:1909.00668 [Cs, Stat]. Retrieved from http://arxiv.org/abs/1909.00668

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

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

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

Kerjean, M., & Pacaud Lemay, J.S. (2019). HigherOrder Distributions for Differential Linear Logic. In M. Bojańczyk & A. Simpson (Eds.), Foundations of Software Science and Computation Structures (pp. 330–347). Cham: Springer International Publishing. https://doi.org/10/ggdmrj

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

Murfet, D. (2018). dmurfet/deeplinearlogic. Retrieved from https://github.com/dmurfet/deeplinearlogic (Original work published 2016)

Fages, F., Martinez, T., Rosenblueth, D. A., & Soliman, S. (2018). Influence Networks Compared with Reaction Networks: Semantics, Expressivity and Attractors. IEEE/ACM Trans. Comput. Biol. Bioinformatics, 15(4), 1138–1151. https://doi.org/10/ggdf94

Murfet, D. (2018). dmurfet/polysemantics. Retrieved from https://github.com/dmurfet/polysemantics (Original work published 2016)

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

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

Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., … Ghahramani, Z. (2017). Denotational validation of higherorder Bayesian inference. Proceedings of the ACM on Programming Languages, 2(POPL), 1–29. https://doi.org/10.1145/3158148

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

Heunen, C., Kammar, O., Staton, S., & Yang, H. (2017). A Convenient Category for HigherOrder Probability Theory. ArXiv:1701.02547 [Cs, Math]. Retrieved from http://arxiv.org/abs/1701.02547

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/10.1007/9783662544341_32

Keimel, K., & Plotkin, G. D. (2017). Mixed powerdomains for probability and nondeterminism. ArXiv:1612.01005 [Cs]. https://doi.org/10/ggdmrp

Jacobs, B., & Zanasi, F. (2017). A Formal Semantics of Influence in Bayesian Reasoning. Schloss Dagstuhl  LeibnizZentrum Fuer Informatik GmbH, Wadern/Saarbruecken, Germany. https://doi.org/10/ggdgbc

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

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
Explore
BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
 Biology (2)
CATEGORICAL LOGIC
 Effectus theory (1)
 Linear logic (14)
DIFFERENTIAL CALCULUS
 Differentiation (5)
MACHINE LEARNING
 Machine Learning (6)
MODEL CHECKING AND STATE MACHINES
 Coalgebras (3)
 Rewriting theory (3)
 Symbolic logic (3)
 Transition systems (8)
PROBABILITY & STATISTICS
PROGRAMMING LANGUAGES
Methodology
 Implementation (5)
Topic
 Abstract machines (3)
 Algebra (2)
 Bayesian inference (2)
 Bayesianism (4)
 Biology (2)
 Categorical ML (4)
 Categorical probability theory (4)
 Coalgebras (3)
 Coherence spaces (4)
 Denotational semantics (21)
 Differential Linear Logic (4)
 Differentiation (5)
 Effectus theory (1)
 Game semantics (2)
 Implementation (5)
 Interactive semantics (2)
 Linear logic (11)
 Machine learning (5)
 Powerdomains (4)
 Probabilistic programming (16)
 Probabilistic transition systems (3)
 Programming language theory (21)
 Rewriting theory (3)
 Semantics (11)
 Symbolic logic (3)
 Systems biology (2)
 Transition systems (4)
 Type theory (1)
Resource type
 Book Section (1)
 Computer Program (3)
 Conference Paper (8)
 Journal Article (25)
 Presentation (1)
Publication year
 Between 1900 and 1999 (4)
 Between 2000 and 2021 (33)
 Unknown (1)