13 citations · 69 across the 11 of their papers we have counts for
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hep-ph2023★ 2 cited
Fitting a Deep Generative Hadronization Model
Jay Chan, Xiangyang Ju, Adam Kania +3
Hadronization is a critical step in the simulation of high-energy particle and nuclear physics experiments. As there is no first principles understanding of this process, physicall…
hep-ph2023★ 5 cited
Parton Labeling without Matching: Unveiling Emergent Labelling Capabilities in Regression Models
Shikai Qiu, Shuo Han, Xiangyang Ju +2
Parton labeling methods are widely used when reconstructing collider events with top quarks or other massive particles. State-of-the-art techniques are based on machine learning an…