411 citations · 657 across the 11 of their papers we have counts for
Showing hep-phShow all
3 papers · 1 filter
hep-ph2022★ 31 cited
Towards a Deep Learning Model for Hadronization
Aishik Ghosh, Xiangyang Ju, Benjamin Nachman +1
Hadronization is a complex quantum process whereby quarks and gluons become hadrons. The widely-used models of hadronization in event generators are based on physically-inspired ph…
hep-ph2022★ 17 cited
A Holistic Approach to Predicting Top Quark Kinematic Properties with the Covariant Particle Transformer
Shikai Qiu, Shuo Han, Xiangyang Ju +2
Precise reconstruction of top quark properties is a challenging task at the Large Hadron Collider due to combinatorial backgrounds and missing information. We introduce a physics-i…
hep-ph2020★ 51 cited
Supervised Jet Clustering with Graph Neural Networks for Lorentz Boosted Bosons
Xiangyang Ju, Benjamin Nachman
Jet clustering is traditionally an unsupervised learning task because there is no unique way to associate hadronic final states with the quark and gluon degrees of freedom that gen…