755 citations · 7.6k across the 89 of their papers we have counts for
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Infrared Finiteness and Forward Scattering
Christopher Frye, Holmfridur Hannesdottir, Nisarga Paul +2
Infrared divergences have long been heralded to cancel in sufficiently inclusive cross-sections, according to the famous Kinoshita-Lee-Nauenberg theorem which mandates an initial a…
JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
Anders Andreassen, Ilya Feige, Christopher Frye +1
In applications of machine learning to particle physics, a persistent challenge is how to go beyond discrimination to learn about the underlying physics. To this end, a powerful to…
Jet Charge and Machine Learning
Katherine Fraser, Matthew D. Schwartz
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For exampl…
Learning to Classify from Impure Samples with High-Dimensional Data
Patrick T. Komiske, Eric M. Metodiev, Benjamin Nachman +1
A persistent challenge in practical classification tasks is that labeled training sets are not always available. In particle physics, this challenge is surmounted by the use of sim…
Factorization Violation and Scale Invariance
Matthew D. Schwartz, Kai Yan, Hua Xing Zhu
Factorization violating effects in hadron scattering are due mainly to spectator-spectator interactions. While it is known that these interactions cancel in inclusive cross section…