HEE Seminar- Taylor Faucett-UCI-Physics Learning from Machines Learning

Date
Dec 1, 2020, 2:00 pm2:00 pm
Location
Via Zoom

Speaker

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Event Description

Abstract: 
Machine Learning methods are extremely powerful but often function as black-box problem solvers, providing improved performance at the expense of clarity. Our work describes a new machine learning approach which translates the strategy of a deep neural network into simple functions that are meaningful and intelligible to the physicist, without sacrificing performance improvements. We apply this approach to benchmark high-energy problems of fat-jet classification and electron identification. In each case, we find simple new observables which provide additional classification power and novel insights into the nature of the problem.