424 citations · 860 across the 26 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
hep-ph2019★ 240 cited
The Machine Learning Landscape of Top Taggers
G. Kasieczka, T. Plehn, A. Butter +24
Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established metho…
hep-ph2019★ 424 cited
ParticleNet: Jet Tagging via Particle Clouds
Huilin Qu, Loukas Gouskos
How to represent a jet is at the core of machine learning on jet physics. Inspired by the notion of point clouds, we propose a new approach that considers a jet as an unordered set…