activity
20162021
most citedThe Tracking Machine Learning challenge : Throughput phase

26 citations · 39 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2021★ 26 cited

The Tracking Machine Learning challenge : Throughput phase

Sabrina Amrouche, Laurent Basara, Paolo Calafiura +18

This paper reports on the second "Throughput" phase of the Tracking Machine Learning (TrackML) challenge on the Codalab platform. As in the first "Accuracy" phase, the participants…

hep-ex2019

The Tracking Machine Learning challenge : Accuracy phase

Sabrina Amrouche, Laurent Basara, Paolo Calafiura +24

This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the tr…

physics.comp-ph2018

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…

astro-ph.HE2017★ 12 cited

Precision measurement of the (e + e) flux in primary cosmic rays from 0.5 GeV to 1 TeV with the Alpha Magnetic Spectrometer on the International Space Station

Manuela Vecchi

We present a precise measurement of the combined electron plus positron flux from 0.5 GeV to 1 TeV, based on the analysis of the data collected by the Alpha Magnetic Spectrometer d…

astro-ph.HE2016★ 1 cited

Precision Measurement of the Proton Flux in Primary Cosmic Rays from 1 GV to 1.8 TV with the Alpha Magnetic Spectrometer on the International Space Station

Cristina Consolandi

A precision measurement of the proton flux in primary cosmic rays with rigidity from 1 GV to 1.8 TV is presented based on 300 million events. The results show that the proton flux…