112 citations · 1.1k across the 29 of their papers we have counts for
7 papers · 1 filter
Novel deep learning methods for track reconstruction
Steven Farrell, Paolo Calafiura, Mayur Mudigonda +11
For the past year, the HEP.TrkX project has been investigating machine learning solutions to LHC particle track reconstruction problems. A variety of models were studied that drew…
Search for nonresonant Higgs boson pair production in the final state at 13 TeV
CMS Collaboration
Results of a search for nonresonant production of Higgs boson pairs, with each Higgs boson decaying to a pair are presented. This search uses data from pro…
Search for pair-produced three-jet resonances in proton-proton collisions at 13 TeV
CMS Collaboration
A search has been performed for pair-produced resonances decaying into three jets. The proton-proton collision data used for this analysis were collected with the CMS detector in 2…
Centrality and pseudorapidity dependence of the transverse energy density in pPb collisions at 5.02 TeV
CMS Collaboration
The almost hermetic coverage of the CMS detector is used to measure the distribution of transverse energy, , over 13.2 units of pseudorapidity, , for pPb collision…
Machine Learning in High Energy Physics Community White Paper
Kim Albertsson, Piero Altoe, Dustin Anderson +125
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by a…
Topology classification with deep learning to improve real-time event selection at the LHC
Thong Q. Nguyen, Daniel Weitekamp, Dustin Anderson +5
We show how event topology classification based on deep learning could be used to improve the purity of data samples selected in real time at at the Large Hadron Collider. We consi…