Media Summary: Machine Learning for the Working Mathematician: Week Five 24 March 2022 Our world is full of surprises, and the same thing can be said of the world of mathematics. Surprises like the icosahedron, ... DeepMind Workshop Topic: Combinatorial Invariance: a Case

Geometric Deep Learning Geordie Williamson - Detailed Analysis & Overview

Machine Learning for the Working Mathematician: Week Five 24 March 2022 Our world is full of surprises, and the same thing can be said of the world of mathematics. Surprises like the icosahedron, ... DeepMind Workshop Topic: Combinatorial Invariance: a Case 해외석학 특별강연 시리즈 2018-10-23.

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Geometric Deep Learning: Geordie Williamson
Geordie Williamson: Neural Networks for Mathematical Discovery (October 29, 2025)
Geordie Williamson "Mental Models for Neural Networks"
AMMI 2022 Course "Geometric Deep Learning" - Seminar 3 (Equivariance in ML) - Geordie Williamson
Geordie Williamson "Searching for interesting mathematical objects with neural networks"
Prof. Geordie Williamson | Human-machine mathematical collaboration with modern AI
Combinatorial Invariance: a Case Study of Pure Math / Machine Learning Inter... - Geordie Williamson
Geordie Williamson: Geometric Representation Theory and the Geometric Satake Equivalence
ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein
Geordie Williamson - What can the working mathematician expect from deep learning? - IPAM at UCLA
Geordie Williamson | Using saliency analysis to discover structure
Geordie Williamson  (Univ. of Sydney) / Representation theory and geometry I
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Geometric Deep Learning: Geordie Williamson

Geometric Deep Learning: Geordie Williamson

Machine Learning for the Working Mathematician: Week Five 24 March 2022

Geordie Williamson: Neural Networks for Mathematical Discovery (October 29, 2025)

Geordie Williamson: Neural Networks for Mathematical Discovery (October 29, 2025)

Our world is full of surprises, and the same thing can be said of the world of mathematics. Surprises like the icosahedron, ...

Geordie Williamson "Mental Models for Neural Networks"

Geordie Williamson "Mental Models for Neural Networks"

Geordie Williamson

AMMI 2022 Course "Geometric Deep Learning" - Seminar 3 (Equivariance in ML) - Geordie Williamson

AMMI 2022 Course "Geometric Deep Learning" - Seminar 3 (Equivariance in ML) - Geordie Williamson

Video recording of the course "

Geordie Williamson "Searching for interesting mathematical objects with neural networks"

Geordie Williamson "Searching for interesting mathematical objects with neural networks"

Geordie Williamson

Prof. Geordie Williamson | Human-machine mathematical collaboration with modern AI

Prof. Geordie Williamson | Human-machine mathematical collaboration with modern AI

Title: Human-

Combinatorial Invariance: a Case Study of Pure Math / Machine Learning Inter... - Geordie Williamson

Combinatorial Invariance: a Case Study of Pure Math / Machine Learning Inter... - Geordie Williamson

DeepMind Workshop Topic: Combinatorial Invariance: a Case

Geordie Williamson: Geometric Representation Theory and the Geometric Satake Equivalence

Geordie Williamson: Geometric Representation Theory and the Geometric Satake Equivalence

MSI Virtual Colloquium:

ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein

ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein

Geometric Deep Learning

Geordie Williamson - What can the working mathematician expect from deep learning? - IPAM at UCLA

Geordie Williamson - What can the working mathematician expect from deep learning? - IPAM at UCLA

Recorded 13 February 2023.

Geordie Williamson | Using saliency analysis to discover structure

Geordie Williamson | Using saliency analysis to discover structure

Mathematics and

Geordie Williamson  (Univ. of Sydney) / Representation theory and geometry I

Geordie Williamson (Univ. of Sydney) / Representation theory and geometry I

해외석학 특별강연 시리즈 2018-10-23.

Behind the Science: Geordie Williamson

Behind the Science: Geordie Williamson

Interview with Professor