catgrad.com

Category Theory × Machine Learning

Paper
Reverse tangent categories
Geoffrey Cruttwell, Jean-Simon Pacaud Lemay
arxiv
permalink
Paper
Data-Parallel Algorithms for String Diagrams
Paul Wilson, Fabio Zanasi
arxivyarrow
permalink
Paper
Computing with Categories in Machine Learning
Eli Sennesh, Tom Xu, Yoshihiro Maruyama
arxivdiscopyroexperiments
permalink
Paper
Categorification of Group Equivariant Neural Networks
Edward Pearce-Crump
arxiv
permalink
Paper
Graph Convolutional Neural Networks as Parametric CoKleisli morphisms
Bruno Gavranović, Mattia Villani
arxiv
permalink
Paper
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory
Dan Shiebler
arxivcode
permalink
Paper
Categorical Foundations of Gradient-Based Learning
G.S.H. Cruttwell, Bruno Gavranović, Neil Ghani, Paul Wilson, Fabio Zanasi
arxivNumeric Optics
permalink
Paper
Learners' languages
David I. Spivak
arxiv
permalink
Talk
Generalised Open Learners
Bruno Gavranović
CyberCat seminar
permalink
Paper
Lenses and Learners
Brendan Fong, Michael Johnson
arxiv
permalink
Paper
Categorical Stochastic Processes and Likelihood
Dan Shiebler
arxivPython Notebook
permalink
Paper
Reverse Derivative Ascent
A Categorical Approach to Learning Boolean Circuits
Paul Wilson, Fabio Zanasi
arxivRDA LibraryExperiments (ACT2020)
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Paper
Functorial Language Games for Question Answering
Giovanni de Felice, Elena Di Lavore, Mario Román, Alexis Toumi
arxiv
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Paper
Poly
An abundant categorical setting for mode-dependent dynamics
David I. Spivak
arxiv
permalink
Paper
Natural Graph Networks
Pim de Haan, Taco Cohen, Max Welling
arxiv
permalink
Paper
Reverse derivative categories
Robin Cockett, Geoffrey Cruttwell, Jonathan Gallagher, Jean-Simon Pacaud Lemay, Benjamin MacAdam, Gordon Plotkin, Dorette Pronk
arxiv
permalink
Paper
The simple essence of automatic differentiation
Conal Elliott
arxivconal.net
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Paper
Backprop as a Functor
A compositional perspective on supervised learning
Brendan Fong, David I. Spivak, Rémy Tuyéras
arxiv
permalink
Paper
Geometric anomaly detection in data
Bernadette J. Stolz, Jared Tanner, Heather A. Harrington, Vidit Nanda
Paper
permalink

Reverse tangent categories

Data-Parallel Algorithms for String Diagrams

Computing with Categories in Machine Learning

Categorification of Group Equivariant Neural Networks

Graph Convolutional Neural Networks as Parametric CoKleisli morphisms

Generalized Optimization: A First Step Towards Category Theoretic Learning Theory

Categorical Foundations of Gradient-Based Learning

Learners' languages

Generalised Open Learners

Lenses and Learners

Categorical Stochastic Processes and Likelihood

Reverse Derivative Ascent

A Categorical Approach to Learning Boolean Circuits

Functorial Language Games for Question Answering

Poly

An abundant categorical setting for mode-dependent dynamics

Natural Graph Networks

Reverse derivative categories

The simple essence of automatic differentiation

Backprop as a Functor

A compositional perspective on supervised learning

Geometric anomaly detection in data