159-page open course notes on e3nn equivariant GNNs released with 60 AI-tutored exercises
burkov · x · 2026-11-08
Mohammad Mostafanejad's 2026 book Equivariant Graph Neural Networks with e3nn is now available as open course notes in Chapter Pal's collection.
e3nn is an open-source, modular PyTorch framework (with a JAX extension, e3nn-jax) providing the math infrastructure for E(3)-equivariant neural networks that natively understand 3D physical space, widely used in molecular and physical ML.
The notes span 159 pages with 42 illustrations and 60 exercises, all wired into an AI tutor for guided learning.
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