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Machine Learning Theory for Physicists

Mainly follow the Jared Kaplan's lectures: ContemporaryMLforPhysicists.pdf
Another very useful review is: A high-bias, low-variance introduction to Machine Learning for physicists 1803.08823
Tishby, Pereira, Bialek, the information bottleneck method: allerton.pdf
The renormalization group applied to neural networks: (https://www.groundai.com/project/neural-network-renormalization-group/1)

There is a github repository with code examples and tutorials (thanks to Ayan Paul).

March 2021

09 Mar - 16 Mar
Ayan Paul, "Interpretable Machine Learning"
02 Mar
Francesco Muia, "Physics -> ML I"

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