activity
20102019
most citedMeasurement of the and cross sections in proton-proton collisions at TeV with the ATLAS detector

94 citations · 126 across the 5 of their papers we have counts for

collaborators

15 papers

hep-ph20193 cited

AI Safety for High Energy Physics

Benjamin Nachman, Chase Shimmin

The field of high-energy physics (HEP), along with many scientific disciplines, is currently experiencing a dramatic influx of new methodologies powered by modern machine learning…

nucl-ex2019

Transverse momentum and process dependent azimuthal anisotropies in TeV +Pb collisions with the ATLAS detector

ATLAS Collaboration

The azimuthal anisotropy of charged particles produced in TeV +Pb collisions is measured with the ATLAS detector at the LHC. The data correspond to…

hep-ex2019

Evidence for electroweak production of two jets in association with a pair in collisions at TeV with the ATLAS detector

ATLAS Collaboration

Evidence for electroweak production of two jets in association with a pair in TeV protonproton collisions at the Large Hadron Collider is presented. The ana…

hep-ex2019

Combined measurements of Higgs boson production and decay using up to fb of proton-proton collision data at 13 TeV collected with the ATLAS experiment

ATLAS Collaboration

Combined measurements of Higgs boson production cross sections and branching fractions are presented. The combination is based on the analyses of the Higgs boson decay modes $H \to…

hep-ex2019

Search for electroweak production of charginos and sleptons decaying into final states with two leptons and missing transverse momentum in TeV collisions using the ATLAS detector

ATLAS Collaboration

A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb of pro…

cs.LG20197 cited

Beyond Imitation: Generative and Variational Choreography via Machine Learning

Mariel Pettee, Chase Shimmin, Douglas Duhaime +1

Our team of dance artists, physicists, and machine learning researchers has collectively developed several original, configurable machine-learning tools to generate novel sequences…