Geometric Deep Learning

This course provides a unified geometric and mathematical foundation for modern deep learning—deriving architectures such as CNNs, GNNs, Transformers, DeepSets, and LSTMs from symmetry and invariance principles—while equipping students with both theoretical understanding and practical insights into their applications.