Advanced Algorithms I
ORAL · APR-H13 · ID: 3098806
Presentations
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Harnessing the power of neural networks to identify and locate primary vertices in ATLAS proton-proton collision data
ORAL
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Presenters
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Qi Bin Lei
- University of Pennsylvania
Authors
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Lauren Tompkins
- Stanford University
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rocky Bala Garg
- Stanford University
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Qi Bin Lei
- University of Pennsylvania
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Semi-leptonic t¯t Calibration of ATLAS GN2X Flavor-Tagging Algorithm
ORAL
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Presenters
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Derrick Allen
- Oklahoma State University
Authors
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Derrick Allen
- Oklahoma State University
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Scaling Salt on Large Machines: Leveraging High-Performance Computing to Train ATLAS Flavor-Tagging Models
ORAL
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Presenters
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Nicholas Luongo
- Argonne National Laboratory
Authors
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Nicholas Luongo
- Argonne National Laboratory
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Evaluation of systematic uncertainties for flavor tagging of jets due to long-lived particle decays at the ATLAS experiment
ORAL
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Presenters
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Soumyananda Goswami
- Oklahoma State University-Stillwater
Authors
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Soumyananda Goswami
- Oklahoma State University-Stillwater
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Alexander Khanov
- Oklahoma State University-Stillwater
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A Data-Driven Geometric Efficiency Correction Technique: Methodology and Application in DUNE
ORAL
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Presenters
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Flynn Guo
- Stony Brook University (SUNY)
Authors
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Flynn Guo
- Stony Brook University (SUNY)
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Wei Shi
- Stony Brook University (SUNY)
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Michael Wilking
- University of Minnesota, Twin Cities
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Cristovao Vilela
- Laboratório de Instrumentação e Física Experimental de Partículas - LIP
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Using Graph Neural Networks for Multi-Detector Particle ID on DUNE’s Near Detector 2x2 Prototype
ORAL
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Presenters
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Jessie Micallef
- Massachusetts Institute of Technology
Authors
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Jessie Micallef
- Massachusetts Institute of Technology
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Panoptic segmentation of NOvA particle detections using a point set transformer
ORAL
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Presenters
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Edgar E Robles
- University of California, Irvine
Authors
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Edgar E Robles
- University of California, Irvine
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Alejandro J Yankelevich
- University of California, Irvine
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Jianming Bian
- University of California, Irvine
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Pierre Baldi
- University of California, Irvine
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Machine Learning Simulation Techniques for the LZ Dark Matter Experiment
ORAL
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Presenters
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Gregory Sehr
- University of Texas at Austin
Authors
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Gregory Sehr
- University of Texas at Austin
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Deep Neural Network MET Reconstruction for the CMS Level-1 Trigger
ORAL
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Presenters
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Daniel Primosch
- UC San Diego
Authors
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Daniel Primosch
- UC San Diego
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