Events

Date: 24 October 2025   Time: 15:30 - 16:30

Location: Room 516, G.O. Jones Building

Machine learning excels at spotting patterns in complex data. In this talk, I will describe how symbolic regression, together with standard ML feature selection methods, rediscovers several well-known analytic results in scattering amplitudes, including the Parke-Taylor, Kleiss-Kuijf, Bern-Carrasco-Johansson, and Kawai-Lewellen-Tye relations, from numerical data and minimal physical priors. This offers an interesting data-driven route to understanding the connection between gauge theories and gravity.