AI RESEARCH
Weaves, Wires, and Morphisms: Formalizing and Implementing the Algebra of Deep Learning
arXiv CS.LG
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ArXi:2604.07242v1 Announce Type: new Despite deep learning models running well-defined mathematical functions, we lack a formal mathematical framework for describing model architectures. Ad-hoc notation, diagrams, and pseudocode poorly handle nonlinear broadcasting and the relationship between individual components and composed models. This paper