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cs.LG2026
Weaves, Wires, and Morphisms: Formalizing and Implementing the Algebra of Deep Learning
Vincent Abbott, Gioele Zardini
Despite deep learning models running well-defined mathematical functions, we lack a formal mathematical framework for describing model architectures. Ad-hoc notation, diagrams, and…
cs.LG2025★ 2 cited
FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness
Vincent Abbott, Gioele Zardini
Optimizing deep learning algorithms currently requires slow, manual derivation, potentially leaving much performance untapped. Methods like FlashAttention have achieved a x6 perfor…
cs.LG2024
Neural Circuit Diagrams: Robust Diagrams for the Communication, Implementation, and Analysis of Deep Learning Architectures
Vincent Abbott
Diagrams matter. Unfortunately, the deep learning community has no standard method for diagramming architectures. The current combination of linear algebra notation and ad-hoc diag…