uvagedl

UvA - An Introduction to Group Equivariant Deep Learning

Welcome to the public page for the mini-course on Group Equivariant Deep Learning. The course is still under development, in the upcoming months I will regularly update them. The most important piece of material in this course are the lecture notes.

Erik Bekkers
Amsterdam Machine Learning Lab (AMLab)
University of Amsterdam






Autumn School on Scientific Machine Learning and Dynamical Systems

For participants of the Autumn School on Scientific Machine Learning and Dynamical Systems, see

Useful libraries:


CODE: Tutorials and other deep learning topics

Video lectures

Youtube playlist:

Lecture slide deck:

Lecture notes

The lecture notes that I wrote when preparing the course are a bit sloppy and contain various typos (my apologies for still not having found the time to fix it). Instead I highly recommend the UvA Master AI thesis by Lars Veefkind. It contains all the essentials for learning about group convolutions, and includes representation theory (Peter-Weyl theorem, Schurr’s Lemma etc.) presented in an accessible and manner!

Other materials

Slides and lecture recording (summer school):

Colab assignments (to be updated…):