Datasets

JetNet
Developed a library for convenient access to jet datasets, and other utilities, to increase accessibility and reproducibility in ML in particle physics. >35,000 downloads as of September 2023, used in several ML and particle physics projects.
JetNet
JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics
JetNet is a Python package that aims to increase accessibility and reproducibility for machine learning (ML) research in high energy …
Raghav Kansal, Carlos Pareja, Javier Duarte
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FAIR AI Models in High Energy Physics
The findable, accessible, interoperable, and reusable (FAIR) data principles have provided a framework for examining, evaluating, and …
Javier Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E. A. Huerta, Daniel Diaz, Philip Harris, Raghav Kansal, Daniel S. Katz, Ishaan H. Kavoori, Volodymyr V. Kindratenko, Farouk Mokhtar, Mark S. Neubauer, Sang Eon Park, Melissa Quinnan, Roger Rusack, Zhizhen Zhao
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JetNet library for machine learning in high energy physics
Sep 16, 2022 Virtual
Project Video Demo
A FAIR and AI-ready Higgs boson decay dataset
To enable the reusability of massive scientific datasets by humans and machines, researchers aim to adhere to the principles of …
Javier Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E. A. Huerta, Daniel Diaz, Philip Harris, Raghav Kansal, Daniel S. Katz, Ishaan H. Kavoori, Volodymyr V. Kindratenko, Farouk Mokhtar, Mark S. Neubauer, Sang Eon Park, Melissa Quinnan, Roger Rusack, Zhizhen Zhao
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Particle Cloud Generation with Message Passing Generative Adversarial Networks
Introduces the message-passing generative adversarial (MPGAN) model and JetNet dataset. We found the physics-informed MPGAN model outperformed all existing point-cloud GANs in simulating high momentum jets.
Raghav Kansal, Javier Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos
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Particle Cloud Generation with Message Passing Generative Adversarial Networks