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math.CT2026

Composable Uncertainty in Symmetric Monoidal Categories for Design Problems

Marius Furter, Yujun Huang, Gioele Zardini

Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, l…

math.CT2025

Composable Uncertainty in Symmetric Monoidal Categories for Design Problems (Extended Version)

Marius Furter, Yujun Huang, Gioele Zardini

Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, l…

math.CT2025

Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks

Vincent Abbott, Kotaro Kamiya, Gerard Glowacki +3

How do we enable artificial intelligence models to improve themselves? This is central to exponentially improving generalized artificial intelligence models, which can improve thei…

math.CT2024

Diagrammatic Negative Information

Vincent Abbott, Gioele Zardini

The flow of information through a complex system can be readily understood with category theory. However, negative information (e.g., what is not possible) does not have an immedia…

math.CT2024

Functor String Diagrams: A Novel Approach to Flexible Diagrams for Applied Category Theory

Vincent Abbott, Gioele Zardini

The study of abstraction and composition - the focus of category theory - naturally leads to sophisticated diagrams which can encode complex algebraic semantics. Consequently, thes…