The first in a two-lecture series on our recently-announced Categorical Deep Learning framework (), given as a lecture for the Geometric Deep Learning (GDL) course at Cambridge.
It offers a quick tutorial through the most important concepts in Category Theory necessary to understand the building blocks of CDL. Assumes prior knowledge of basics of geometric deep learning, group theory and representation theory.
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