1.2k citations · 4.5k across the 78 of their papers we have counts for
3 papers · 2 filters
Jet Flavor Classification in High-Energy Physics with Deep Neural Networks
Daniel Guest, Julian Collado, Pierre Baldi +3
Classification of jets as originating from light-flavor or heavy-flavor quarks is an important task for inferring the nature of particles produced in high-energy collisions. The la…
Jet Substructure Classification in High-Energy Physics with Deep Neural Networks
Pierre Baldi, Kevin Bauer, Clara Eng +2
At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets ove…
Parameterized Machine Learning for High-Energy Physics
Pierre Baldi, Kyle Cranmer, Taylor Faucett +2
We investigate a new structure for machine learning classifiers applied to problems in high-energy physics by expanding the inputs to include not only measured features but also ph…