Your search
Publication year
Online resource
Results
104 resources-
Wilkinson, D. (2019, August 7). Write your own general-purpose monadic probabilistic programming language from scratch in 50 lines of (Scala) code. Retrieved November 27, 2019, from https://darrenjw.wordpress.com/2019/08/07/write-your-own-general-purpose-monadic-probabilistic-programming-language-from-scratch-in-50-lines-of-scala-code/
-
Paul, A., & Venkatasubramanian, S. (2015). Why does Deep Learning work? - A perspective from Group Theory. ArXiv:1412.6621 [Cs, Stat]. Retrieved from http://arxiv.org/abs/1412.6621
-
McCullagh, P. (2002). What is a statistical model? The Annals of Statistics, 30(5), 1225–1310. https://doi.org/10/bkts3m
-
Tsuchiya, N., Taguchi, S., & Saigo, H. (2016). Using category theory to assess the relationship between consciousness and integrated information theory. Neuroscience Research, 107, 1–7. https://doi.org/10/ggdf95
-
Rutten, J. J. M. M. (2000). Universal coalgebra: a theory of systems. Theoretical Computer Science, 249(1), 3–80. https://doi.org/10/fqrjpn
-
Zhang, C., Bengio, S., Hardt, M., Recht, B., & Vinyals, O. (2017). Understanding deep learning requires rethinking generalization. ArXiv:1611.03530 [Cs]. Retrieved from http://arxiv.org/abs/1611.03530
-
Jacobs, B., & Furber, R. (2015). Towards a Categorical Account of Conditional Probability. Electronic Proceedings in Theoretical Computer Science, 195, 179–195. https://doi.org/10/ggdf9w
-
Hess, K., Dotko, P., Levi, R., Nolte, M., Reimann, M., Scolamiero, M., … Markram, H. (2017). Topological analysis of the connectome of digital reconstructions of neural microcircuits. Frontiers in Computational Neuroscience, 11, 48. https://doi.org/10/gdjbfn
-
Poggio, T. (2013). Tomaso A. Poggio autobiography (p. 54). Retrieved from http://poggio-lab.mit.edu/sites/default/files/cv/tomasopoggio.pdf
-
Mazzola, G. (2002). The Topos of Music: Geometric Logic of Concepts, Theory, and Performance. Birkhäuser Basel. https://doi.org/10.1007/978-3-0348-8141-8
-
Elliott, C. (2018). The simple essence of automatic differentiation. ArXiv:1804.00746 [Cs]. Retrieved from http://arxiv.org/abs/1804.00746
-
Jacobs, B., & Zanasi, F. (2018). The Logical Essentials of Bayesian Reasoning. ArXiv:1804.01193 [Cs]. Retrieved from http://arxiv.org/abs/1804.01193
-
Boutillier, P., Maasha, M., Li, X., Medina-Abarca, H. F., Krivine, J., Feret, J., … Fontana, W. (2018). The Kappa platform for rule-based modeling. Bioinformatics, 34(13), i583–i592. https://doi.org/10/gdrhw6
-
Ehrhard, T., & Regnier, L. (2003). The differential lambda-calculus. Theoretical Computer Science, 309(1), 1–41. https://doi.org/10/bf3b8v
-
Jacobs, B., & Sprunger, D. (2019). The differential calculus of causal functions. ArXiv:1904.10611 [Cs]. Retrieved from http://arxiv.org/abs/1904.10611
-
Vytiniotis, D., Belov, D., Wei, R., Plotkin, G., & Abadi, M. (2019). The Differentiable Curry. Retrieved from https://openreview.net/forum?id=ryxuz9SzDB
-
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
-
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
-
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
-
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
Explore
BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
- Biology (11)
- Neuroscience (9)
- Psychology (4)
CATEGORICAL LOGIC
- Effectus theory (8)
- Linear logic (15)
DIFFERENTIAL CALCULUS
- Differentiation (15)
MACHINE LEARNING
- Machine Learning (34)
MODEL CHECKING AND STATE MACHINES
- Coalgebras (6)
- Rewriting theory (5)
- Symbolic logic (5)
- Transition systems (15)
PROBABILITY & STATISTICS
PROGRAMMING LANGUAGES
- Programming language theory (43)
- Type theory (4)
Methodology
- Compendium (2)
- Implementation (18)
- Sketchy (8)
Topic
- Abstract machines (7)
- Adversarial attacks (5)
- Algebra (3)
- Automatic differentiation (6)
- Bayesian inference (7)
- Bayesianism (14)
- Biology (7)
- Categorical ML (10)
- Categorical probability theory (14)
- Classical ML (13)
- Coalgebras (6)
- Coherence spaces (4)
- Compendium (2)
- Denotational semantics (14)
- Differential Linear Logic (6)
- Differentiation (15)
- Effectus theory (8)
- Emergence (5)
- Game semantics (2)
- Implementation (15)
- Interactive semantics (3)
- Linear logic (12)
- Machine learning (25)
- Neuroscience (8)
- Powerdomains (3)
- Probabilistic programming (21)
- Probabilistic transition systems (5)
- Programming language theory (23)
- Psychology (4)
- Purely theoretical (7)
- Rewriting theory (5)
- Semantics (10)
- Sketchy (6)
- Statistical learning theory (2)
- Symbolic logic (5)
- Systems biology (3)
- Topological data analysis (4)
- Transition systems (6)
- Type theory (1)
Resource type
- Blog Post (1)
- Book (1)
- Book Section (5)
- Computer Program (4)
- Conference Paper (6)
- Journal Article (85)
- Manuscript (1)
- Web Page (1)