Origins of Geometric Deep Learning - Part 2 and 3

A while ago we referenced the first article of the series on the Origins of Geometric DL by Michael Bronstein. Recently, the series got new episodes - Part 2 focuses on the high hopes about the perceptron, the curse of dimensionality, and first AI winters. Part 3 introduces first architectures with baked geometrical priors - the neocognitron (precursor of convnets) and convolutional neural networks.

As always, Michael did a great and meticulous job of finding original references and adding some comments to them - often the references section is as interesting and informative as the main text! 🍿