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20152025
most citedClassification without labels: Learning from mixed samples in high energy physics

297 citations · 436 across the 7 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

hep-ph2019

OmniFold: A Method to Simultaneously Unfold All Observables

Anders Andreassen, Patrick T. Komiske, Eric M. Metodiev +2

Collider data must be corrected for detector effects ("unfolded") to be compared with many theoretical calculations and measurements from other experiments. Unfolding is traditiona…

hep-ph201920 cited

Cutting Multiparticle Correlators Down to Size

Patrick T. Komiske, Eric M. Metodiev, Jesse Thaler

Multiparticle correlators are mathematical objects frequently encountered in quantum field theory and collider physics. By translating multiparticle correlators into the language o…

hep-ph2019

Exploring the Space of Jets with CMS Open Data

Patrick T. Komiske, Radha Mastandrea, Eric M. Metodiev +2

We explore the metric space of jets using public collider data from the CMS experiment. Starting from 2.3/fb of 7 TeV proton-proton collisions collected at the Large Hadron Collide…

hep-ph2019

A Theory of Quark vs. Gluon Discrimination

Andrew J. Larkoski, Eric M. Metodiev

Understanding jets initiated by quarks and gluons is of fundamental importance in collider physics. Efficient and robust techniques for quark versus gluon jet discrimination have c…

hep-ph2019

The Machine Learning Landscape of Top Taggers

G. Kasieczka, T. Plehn, A. Butter +24

Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established metho…

hep-ph2019

The Metric Space of Collider Events

Patrick T. Komiske, Eric M. Metodiev, Jesse Thaler

When are two collider events similar? Despite the simplicity and generality of this question, there is no established notion of the distance between two events. To address this que…