8 citations · 10 across the 4 of their papers we have counts for
5 papers
Fundamental Components of Deep Learning: A category-theoretic approach
Bruno Gavranović
Deep learning, despite its remarkable achievements, is still a young field. Like the early stages of many scientific disciplines, it is marked by the discovery of new phenomena, ad…
Graph Convolutional Neural Networks as Parametric CoKleisli morphisms
Bruno Gavranović, Mattia Villani
We define the bicategory of Graph Convolutional Neural Networks for an arbitrary graph with nodes. We show it can be factored through the already existing cat…
Space-time tradeoffs of lenses and optics via higher category theory
Bruno Gavranović
Optics and lenses are abstract categorical gadgets that model systems with bidirectional data flow. In this paper we observe that the denotational definition of optics - identifyin…
Category Theory in Machine Learning
Dan Shiebler, Bruno Gavranović, Paul Wilson
Over the past two decades machine learning has permeated almost every realm of technology. At the same time, many researchers have begun using category theory as a unifying languag…
Categorical Foundations of Gradient-Based Learning
G. S. H. Cruttwell, Bruno Gavranović, Neil Ghani +2
We propose a categorical semantics of gradient-based machine learning algorithms in terms of lenses, parametrised maps, and reverse derivative categories. This foundation provides…