# Your search

PROGRAMMING LANGUAGES

Resource type

## Results

25 resources-
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 -
Ehrhard, T. (2019). Differentials and distances in probabilistic coherence spaces.
*ArXiv:1902.04836 [Cs]*. Retrieved from http://arxiv.org/abs/1902.04836 -
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 -
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 -
Ehrhard, T., & Tasson, C. (2018). Probabilistic call by push value.
*ArXiv:1607.04690 [Cs]*. https://doi.org/10/ggdk8z -
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 -
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 Higher-Order Probability Theory.
*ArXiv:1701.02547 [Cs, Math]*. Retrieved from http://arxiv.org/abs/1701.02547 -
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 - Leibniz-Zentrum 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: proof-nets, models and antiderivatives.
*ArXiv:1606.01642 [Cs]*. Retrieved from http://arxiv.org/abs/1606.01642 -
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 -
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 -
Keimel, K., & Plotkin, G. d. (2009). Predicate Transformers for Extended Probability and Non-determinism.
*Mathematical. Structures in Comp. Sci.*,*19*(3), 501–539. https://doi.org/10/bkvgqc -
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 -
Fiore, M., Gambino, N., Hyland, M., & Winskel, G. (2008). The cartesian closed bicategory of generalised species of structures.
*Journal of the London Mathematical Society*,*77*(1), 203–220. https://doi.org/10/bd2mr9 -
Fages, F., Calzone, L., & Soliman, S. (2006). BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge.
*Bioinformatics*,*22*(14), 1805–1807. https://doi.org/10/dfv -
Varacca, D., & Winskel, G. (2006). Distributing probability over non-determinism.
*Mathematical Structures in Computer Science*,*16*(01), 87. https://doi.org/10/czs9sx

## Explore

### BIOLOGY, NEUROSCIENCE & PSYCHOLOGY

- Biology (2)

### CATEGORICAL LOGIC

- Effectus theory (1)
- Linear logic (7)

### DIFFERENTIAL CALCULUS

- Differentiation (4)

### MACHINE LEARNING

- Machine Learning (2)

### MODEL CHECKING AND STATE MACHINES

- Coalgebras (2)
- Rewriting theory (2)
- Symbolic logic (3)
- Transition systems (5)

### PROBABILITY & STATISTICS

### PROGRAMMING LANGUAGES

### Methodology

- Implementation (2)

### Topic

- Abstract machines (2)
- Algebra (1)
- Bayesian inference (1)
- Bayesianism (3)
- Biology (2)
- Categorical ML (1)
- Categorical probability theory (3)
- Coalgebras (2)
- Coherence spaces (2)
- Denotational semantics (14)
- Differential Linear Logic (3)
- Differentiation (4)
- Effectus theory (1)
- Implementation (2)
- Linear logic (6)
- Machine learning (1)
- Powerdomains (3)
- Probabilistic programming (9)
- Probabilistic transition systems (2)
- Programming language theory (14)
- Rewriting theory (2)
- Semantics (5)
- Symbolic logic (3)
- Systems biology (2)
- Transition systems (2)
- Type theory (1)