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09/13/2023
Scalable neural network models and terascale datasets for particle-flow reconstruction
We study scalable machine learning models for full event reconstruction ...
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03/30/2023
Progress towards an improved particle flow algorithm at CMS with machine learning
The particle-flow (PF) algorithm, which infers particles based on tracks...
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12/09/2022
FAIR AI Models in High Energy Physics
The findable, accessible, interoperable, and reusable (FAIR) data princi...
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11/17/2022
Do graph neural networks learn traditional jet substructure?
At the CERN LHC, the task of jet tagging, whose goal is to infer the ori...
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03/01/2022
Machine Learning for Particle Flow Reconstruction at CMS
We provide details on the implementation of a machine-learning based par...
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11/24/2021
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
Autoencoders have useful applications in high energy physics in anomaly ...
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11/24/2021
