most citedMachine learning approach for the search of resonances with topological features at the Large Hadron Collider

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

hep-ex2021

An investigation of over-training within semi-supervised machine learning models in the search for heavy resonances at the LHC

Benjamin Lieberman, Joshua Choma, Salah-Eddine Dahbi +2

In particle physics, semi-supervised machine learning is an attractive option to reduce model dependencies searches beyond the Standard Model. When utilizing semi-supervised techni…

hep-ex2020★ 2 cited

Machine learning approach for the search of resonances with topological features at the Large Hadron Collider

Salah-eddine Dahbi, Joshua Choma, Bruce Mellado +4

The observation of resonances is unequivocal evidence of new physics beyond the Standard Model at the Large Hadron Collider (LHC). So far, inclusive and model dependent searches ha…