AMMI Course “Geometric Deep Learning“ - Lecture 9 (Manifolds & Meshes) - Michael Bronstein

Video recording of the course “Geometric Deep Learning“ taught in the African Master in Machine Intelligence in July-August 2021 by Michael Bronstein (Imperial College/Twitter), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 9: Euclidean vs Non-Euclidean convolution • Manifolds • Tangent vectors • Riemannian metric • Geodesics • Parallel transport • Exponential map • Convolution on manifolds • Domain deformation • Pushfowards and Pullback • Isometries • Deformation invariance • Scalar and vector fields • Gradient, Divergence, and Laplacian operators • Heat and Wave equations • Manifold Fourier transform • Spectral convolution • Meshes • Discrete Laplacians • ChebNet • Graph Convolutional Network • sGCN • SIGN Slides: Additional materials: