Skip to content

kartikchincholikar/Geometric-deep-learning-sources

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

30 Commits
 
 

Repository files navigation

Geometric-deep-learning-sources

A collection of resources to help beginners get started with geometric deep learning

Podcasts

Geometric Deep Learning Blueprint
A conversation with Professor Michael Bronstein, Dr. Petar Veličković, Dr. Taco Cohen and Prof. Joan Bruna

Machine Learning Street Talk- Quantum, Manifolds & Symmetries in ML
A conversation with Professor Max Welling

Towards Data Science
A conversation with Professor Max Welling

The TWIML AI Podcast
A conversation with Professor Michael Bronstein and Prof. Joan Bruna

Geometry, Geometry and more Geometry with Dr. Matthew Satriano
A conversation with Professor Dr. Matthew Satriano

A short history of symmetry
In this podcast series Professor Ian Stewart of Warwick's Department of Mathematics explores the history of symmetry and its impact on mathematics, physics and our understanding of the Universe.

Stand alone Lectures / Talks

ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein
Workshop on Equivariance and Data Augmentation
Theoretical Foundations of Graph Neural Networks
Geometric Deep Learning: GNNs Beyond Permutation Equivariance
Symmetries of the Universe | ScienceClic
CIS COLLOQUIUM: Prof. Michael Bronstein - Geometric Deep Learning: from Euclid to drug design
Max Welling Talk on Graphs
Geometric Deep Learning: Geordie Williamson

Lecture Series

Deep Learning
Group Equivariant Deep Learning
Equivariant Neural Networks | Short Video Serier by DeepFindr
Pytorch Geometric tutorial
AMMI 2022 Course "Geometric Deep Learning"
First Italian School on Geometric Deep Learning - Pescara 2022
Multi Task and Meta Learning
Graphs and Geometry Reading Group
Euclidian Symmetry in Machine Learning for Material Science
Stanford CS330: Deep Multi-Task & Meta Learning

Math Lecture Series

Visual Group Theory
Group Theory - Richard E. BORCHERDS
You Could Have Invented Homology
Categories for AI\

Stand alone Lectures / Talks

ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein
Workshop on Equivariance and Data Augmentation
Theoretical Foundations of Graph Neural Networks
Geometric Deep Learning: GNNs Beyond Permutation Equivariance
Symmetries of the Universe | ScienceClic
CIS COLLOQUIUM: Prof. Michael Bronstein - Geometric Deep Learning: from Euclid to drug design
Max Welling Talk on Graphs
Geometric Deep Learning: Geordie Williamson
Symmetry and Equivariance in Neural Networks - Tess Smidt

Books

Geometric Deep Learning Proto Book
Equivariance For Deep Learning And Retinal Imaging
Improving training of deep learning for biomedical image analysis and computational physics
Deep Learning for Molecules and Materials\

Blogs

Conv Nets: A Modular Perspective
Understanding Convolutions
Groups & Group Convolutions
Geometric foundations of Deep Learning
Noethers Theorem | Fabian Fuchs
Equivariance part 1 | Fabian Fuchs
Equivariance part 2 | Fabian Fuchs
Naturally Occurring Equivariance in Neural Networks
Aleksa Gordic | Introduction to Graph Attention Networks\

Seeing transformers as graphs

Aman.ai
Transformers are Graph Neural Networks
DeepMind x UCL | Deep Learning Lectures | 7/12 | Deep Learning for Natural Language Processing
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective

About

A collection of resources to help beginners get started with geometric deep learning

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors