16 citations · 32 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
The Cost of Compositionality: A High-Performance Implementation of String Diagram Composition
Paul Wilson, Fabio Zanasi
String diagrams are an increasingly popular algebraic language for the analysis of graphical models of computations across different research fields. Whereas string diagrams have b…
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…
Reverse Derivative Ascent: A Categorical Approach to Learning Boolean Circuits
Paul Wilson, Fabio Zanasi
We introduce Reverse Derivative Ascent: a categorical analogue of gradient based methods for machine learning. Our algorithm is defined at the level of so-called reverse differenti…