no code implementations • 25 Nov 2022 • Harrison Mitchell, Alexander Norcliffe, Pietro Liò
In the wake of the growing popularity of machine learning in particle physics, this work finds a new application of geometric deep learning on Feynman diagrams to make accurate and fast matrix element predictions with the potential to be used in analysis of quantum field theory.