Compositional Deep Learning. - Bruno Gavranovic (CoRR, 2019)

Learning Functors using Gradient Descent. - Bruno Gavranovic (ACT, 2019)

Compositional Game Theory, Compositionally. - Robert Atkey; Bruno Gavranovic; Neil Ghani; Clemens Kupke; Jérémy Ledent; Fredrik Nordvall Forsberg (ACT, 2020)

Towards Foundations of Categorical Cybernetics. - Matteo Capucci; Bruno Gavranovic; Jules Hedges; Eigil Fjeldgren Rischel (ACT, 2021)

Category Theory in Machine Learning. - Dan Shiebler; Bruno Gavranovic; Paul W. Wilson 002 (CoRR, 2021)

Categorical Foundations of Gradient-Based Learning. - Geoffrey S. H. Cruttwell; Bruno Gavranovic; Neil Ghani; Paul W. Wilson 002; Fabio Zanasi (ESOP, 2022)

Space-time tradeoffs of lenses and optics via higher category theory. - Bruno Gavranovic (CoRR, 2022)

Graph Convolutional Neural Networks as Parametric CoKleisli morphisms. - Bruno Gavranovic; Mattia Villani (CoRR, 2022)

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures. - Bruno Gavranovic; Paul Lessard; Andrew Joseph Dudzik; Tamara von Glehn; João Guilherme Madeira Araújo; Petar Velickovic (ICML, 2024)

Categorical Deep Learning: An Algebraic Theory of Architectures. - Bruno Gavranovic; Paul Lessard; Andrew Dudzik; Tamara von Glehn; João G. M. Araújo; Petar Velickovic (CoRR, 2024)

Fundamental Components of Deep Learning: A category-theoretic approach. - Bruno Gavranovic (CoRR, 2024)

On a fibrational construction for optics, lenses, and Dialectica categories. - Matteo Capucci; Bruno Gavranovic; Abdullah Malik; Francisco Rios; Jonathan Weinberger (CoRR, 2024)

Deep Learning with Parametric Lenses. - Geoffrey S. H. Cruttwell; Bruno Gavranovic; Neil Ghani; Paul W. Wilson 002; Fabio Zanasi (CoRR, 2024)