🔥 New Course: An Introduction to Group Equivariant Deep Learning

Erik Bekkers from University of Amsterdam created a fantastic new course covering the most up-to-date flavor of GNNs, namely, equivariant and group-equivariant GNNs. The course consists of 3 lectures, starts from the introduction to the group theory, gradually comes to equivariance and steerable kernels, covers tensor products and irreducible representations (hello Wigner matrices). After the course, you won’t be afraid of cryptic abbreviation like SO(3) or E(n)!

The course includes a YouTube playlist, slides, lecture notes, and Colab notebooks to play around with the real code.

If you got inspired by this topic, we highly recommend the upcoming course by Joey Bose (Mila and McGill) on Geometry and Generative Models with even deeper study of manifolds (hyperbolic, spherical, product) to normalizing flows, ODEs, and denoising diffusion models.