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hep-ph2026
The Living Guide of Machine Learning for Particle Physics
Claudius Krause, Ramon Winterhalder, Matthew Feickert +1
We started the Living Review of Machine Learning for Particle Physics (HEP-ML Living Review) in 2020 as a community-maintained, near-comprehensive bibliography of machine learning…
hep-ph2026
pylhe: A Lightweight Python interface to Les Houches Event files
Alexander Puck Neuwirth, Matthew Feickert, Lukas Heinrich +1
Les Houches Event files are a standard format for Monte Carlo event generators in high-energy physics. pylhe is a lightweight pure-Python library for reading and writing LHE event…
hep-ph2025
Reinterpretation and preservation of data and analyses in HEP
Jon Butterworth, Sabine Kraml, Harrison Prosper +145
Data from particle physics experiments are unique and are often the result of a very large investment of resources. Given the potential scientific impact of these data, which goes…