240 citations · 1.9k across the 47 of their papers we have counts for
5 papers · 1 filter
Targeting Multi-Loop Integrals with Neural Networks
Ramon Winterhalder, Vitaly Magerya, Emilio Villa +5
Numerical evaluations of Feynman integrals often proceed via a deformation of the integration contour into the complex plane. While valid contours are easy to construct, the numeri…
Classification of Fermi-LAT blazars with Bayesian neural networks
Anja Butter, Thorben Finke, Felicitas Keil +2
The use of Bayesian neural networks is a novel approach for the classification of gamma-ray sources. We focus on the classification of Fermi-LAT blazar candidates, which can be div…
Generative Networks for Precision Enthusiasts
Anja Butter, Theo Heimel, Sander Hummerich +4
Generative networks are opening new avenues in fast event generation for the LHC. We show how generative flow networks can reach percent-level precision for kinematic distributions…
Presenting Unbinned Differential Cross Section Results
Miguel Arratia, Anja Butter, Mario Campanelli +10
Machine learning tools have empowered a qualitatively new way to perform differential cross section measurements whereby the data are unbinned, possibly in many dimensions. Unbinne…
Back to the Formula -- LHC Edition
Anja Butter, Tilman Plehn, Nathalie Soybelman +1
While neural networks offer an attractive way to numerically encode functions, actual formulas remain the language of theoretical particle physics. We show how symbolic regression…