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New paper suggestion for study: "A correspondence between Random neural networks and statistical field theory"

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Hey,

as I am strong supporter of "Depth First Learning" and am very intrigued by the material, I wanted
to suggest to include a curriculum on "A correspondence between Random neural networks and statistical field theory" (Pennington, Schoenholz, 2017).

Even though there are some more recent developments on statistical field theory for neural networks (e.g. Helias, Dahmen, 2020 or Grosvenor, Jefferson, 2021) I think, that the paper of Pennington and Schoenholz provides rich opportunities to create a curriculum which covers not only NN and statistical field theory but also some basic introduction in to replica methods.

As the publication is in the realm of materials which I study for my PhD, I could design a curriculum.
Greetings
Javed (Lindner), (PhD student, RWTH Aachen University)