Speaker
Anja Butter
Description
We propose a novel method to subtract distributions represented by samples. We train a subGAN that takes event samples from two distributions to generate samples filling the difference between the distributions. While the algorithm can have various applications for Monte Carlo methods, we illustrate its performance for Z + jets NLO event generation.
Primary authors
Anja Butter
Tilman Plehn
Ramon Winterhalder
(Universität Heidelberg)
