Geometric Deep Learning
Max explains the concept of geometric deep learning, focusing on data structures beyond Euclidean spaces. He delves into the abstraction needed for neural networks to work on non-Euclidean data, highlighting the importance of recognizing symmetries in different manifolds.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#036 - Max Welling: Quantum, Manifolds & Symmetries in ML
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