JetNet: A Python Package for Accessing Open Datasets and Benchmarking Machine Learning Methods in High Energy Physics

Raghav Kansal, Carlos Pareja, Zichun Hao, Javier Duarte

Published in the Journal of Open Source Software, volume 8, issue 90, page 5789 (2023).

Summary

JetNet is a Python package that aims to increase accessibility and reproducibility for machine learning (ML) research in high energy physics (HEP), primarily related to particle jets. Based on the popular PyTorch ML framework, it provides easy-to-access and standardized interfaces for multiple heterogeneous HEP datasets and implementations of evaluation metrics, loss functions, and more general utilities relevant to HEP.

Links

• Paper (JOSS)
• Code on GitHub
• Documentation

Cite

@article{Kansal2023jetnet,
    author = "Kansal, Raghav and Pareja, Carlos and Hao, Zichun and Duarte, Javier",
    title = "{JetNet: A Python package for accessing open datasets and benchmarking machine learning methods in high energy physics}",
    journal = "Journal of Open Source Software",
    volume = "8",
    number = "90",
    pages = "5789",
    year = "2023",
    doi = "10.21105/joss.05789"
}