Title says it all. I am looking for great theories which explain how neural networks learn and why they work as good as they do. Every theory should also make predictions (quantum theory can be used to predict the molecular interactions, etc. . relativity theory predicts the behaviour of space-time. etc.).
I know of the following theories which are worth to mention:
https://arxiv.org/pdf/1503.02406.pdf "Deep Learning and the Information Bottleneck Principle"
https://arxiv.org/pdf/2104.13478.pdf "Geometric Deep Learning - Grids, Groups, Graphs, Geodesics, and Gauges"
https://arxiv.org/pdf/2106.10165.pdf "The Principles of Deep Learning Theory"
anything else important I was missing?
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