86 citations · 788 across the 29 of their papers we have counts for
12 papers · 1 filter
Data-driven Estimation of Background Distribution through Neural Autoregressive Flows
Suyong Choi, Jaehoon Lim, Hayoung Oh
We report on a general and automatic data-driven background distribution shape estimation method using neural autoregressive flows (NAF), which is one of the deep generative learni…
Improved Extrapolation Methods of Data-driven Background Estimation in High-Energy Physics
Suyong Choi, Hayoung Oh
Data-driven methods of background estimations are often used to obtain more reliable descriptions of backgrounds. In hadron collider experiments, data-driven techniques are used to…
Infrared Safety of a Neural-Net Top Tagging Algorithm
Suyong Choi, Seung J. Lee, Maxim Perelstein
Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent p…
Implications of LHC data on 125GeV Higgs-like boson for the Standard Model and its various extensions
Suyong Choi, Sunghoon Jung, P. Ko
Recent data on 125 GeV Higgs-like boson at the LHC starts to constrain the electroweak symmetry breaking sector of the SM and its various extensions. If one imposes the local gauge…
Azimuthal decorrelation in production at hadron colliders
Suyong Choi, Hyun Su Lee
We present a new observable, , an azimuthal angle difference between and quarks in pair production, at hadron colliders as an interesting probe of the…
Probing Higgs in Type III Seesaw at the LHC
Priyotosh Bandyopadhyay, Suyong Choi, Eung Jin Chun +1
We show that the type III seesaw mechanism opens up a promising possibility of searching the Higgs boson in the channel through the Higgs production associated with a ch…