Your search
Methodology
Results
18 resources
Harris, K. D. (2019). Characterizing the invariances of learning algorithms using category theory. ArXiv:1905.02072 [Cs, Math, Stat]. Retrieved from http://arxiv.org/abs/1905.02072

Heller, M. (2019). Homunculus’ Brain and Categorical Logic. ArXiv, abs/1903.03424.

MartinMaroto, F., & de Polavieja, G. G. (2018). Algebraic Machine Learning. ArXiv:1803.05252 [Cs, Math]. Retrieved from http://arxiv.org/abs/1803.05252

Mascari, J.F., Giacchero, D., & Sfakianakis, N. (2017). Symetries and asymetries of the immune system response: A categorification approach. In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1451–1454). https://doi.org/10/ggdnd3

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

Ehresmann, A. C., & GomezRamirez, J. (2015). Conciliating neuroscience and phenomenology via category theory. Progress in Biophysics and Molecular Biology, 119(3), 347–359. https://doi.org/10/f75jzr

Andreatta, M., Ehresmann, A., Guitart, R., & Mazzola, G. (2013). Towards a Categorical Theory of Creativity for Music, Discourse, and Cognition. In J. Yust, J. Wild, & J. A. Burgoyne (Eds.), Mathematics and Computation in Music (pp. 19–37). Berlin, Heidelberg: Springer. https://doi.org/10/ggdndz

Gómez, J. (2009). Modeling cognitive systems with Category Theory Towards rigor in cognitive sciences.

Brown, R., & Porter, T. (2008). Category Theory and Higher Dimensional Algebra: potential descriptive tools in neuroscience. ArXiv:Math/0306223. Retrieved from http://arxiv.org/abs/math/0306223

Engeler, E. (2008). Neural Algebra and Consciousness: A Theory of Structural Functionality in Neural Nets. In K. Horimoto, G. Regensburger, M. Rosenkranz, & H. Yoshida (Eds.), Algebraic Biology (Vol. 5147, pp. 96–109). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/9783540851011_8

Healy, M. J., & Caudell, T. P. (2004). Neural Networks, Knowledge and Cognition: A Mathematical Semantic Model Based upon Category Theory.

Mazzola, G. (2002). The Topos of Music: Geometric Logic of Concepts, Theory, and Performance. Birkhäuser Basel. https://doi.org/10.1007/9783034881418

Kato, G. C., & Struppa, D. C. (2002). Category Theory and Consciousness. https://doi.org/10/ggdf92

Healy, M. J. (2000). Category theory applied to neural modeling and graphical representations. In Proceedings of the IEEEINNSENNS 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

Lawvere, F. W. (1994). Tools for the Advancement of Objective Logic: Closed Categories and Toposes. In J. Macnamara & G. E. Reyes (Eds.), The Logical Foundations of Cognition (pp. 43–56). Oxford University Press USA.

Rosen, R. (1958). The representation of biological systems from the standpoint of the theory of categories. The Bulletin of Mathematical Biophysics, 20(4), 317–341. https://doi.org/10/fdgzxz

Murfet, D. (n.d.). Algebra and Artiﬁcial Intelligence.

Gromov, M. (n.d.). Structures, Learning and Ergosystems: Chapters, 159.
Explore
BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
 Biology (13)
 Neuroscience (8)
 Psychology (5)
MACHINE LEARNING
 Machine Learning (4)
MODEL CHECKING AND STATE MACHINES
 Rewriting theory (1)
Methodology
 Compendium (2)
 Sketchy
Topic
 Algebra (1)
 Biology (4)
 Classical ML (1)
 Compendium (2)
 Emergence (10)
 Machine learning (1)
 Neuroscience (6)
 Psychology (5)
 Rewriting theory (1)
 Sketchy (14)
Resource type
 Book (1)
 Book Section (2)
 Conference Paper (6)
 Journal Article (8)
 Presentation (1)
Publication year
 Between 1900 and 1999 (2)
 Between 2000 and 2020 (14)
 Unknown (2)