As part of the African Master’s in Machine Intelligence (AMMI 2021), we have delivered a course on Geometric Deep Learing (GDL100), which closely follows the contents of our GDL proto-book. We make all materials and artefacts from this course publicly available, as companion material for our proto-book, as well as a way to dive deeper into some of the contents for future iterations of the book.
All lecture recordings
| Tutorial 1: Graph Neural Networks |
Pim de Haan, Nikola Jovanović |
Recording |
Colab |
| Tutorial 2: Group Equivariant Neural Networks |
Gabriele Cesa |
Recording |
Colab |
| Seminar 1: Geometric Deep Learning and Reinforcement Learning |
Elise van der Pol |
Recording |
Slides |
| Seminar 2: Natural Graph Networks |
Pim de Haan |
Recording |
Slides (coming soon!) |
| Seminar 3: General E(2)-Equivariant Steerable CNNs |
Gabriele Cesa |
Recording |
Slides (coming soon!) |
| Seminar 4: Weisfeiler and Lehman go Topological: Message Passing Simplicial Networks |
Fabrizio Frasca |
Recording (coming soon!) |
Slides |