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Physical Review D

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J. High Energ. Phys. (2)Phys. Rev. D (1)

Articles Citing

Unbinned inclusive cross-section measurements with machine-learned systematic uncertainties

Lisa Benato , Cristina Giordano , Claudius Krause , Ang Li , Robert Schöfbeck , Dennis Schwarz , Maryam Shooshtari , and Daohan Wang

Institute for High Energy Physics, Austrian Academy of Sciences Dominikanerbastei 16, 1010 Vienna, Austria

Optimizing the cut and count method in phenomenological studies

Baradhwaj Coleppa, Gokul B. Krishna, Agnivo Sarkar, and Sujay Shil

Phys. Rev. D 113 095020 (2026)

Observable optimization for precision theory: machine learning energy correlators

Arindam Bhattacharya, Katherine Fraser, and Matthew D. Schwartz

J. High Energ. Phys. 2026 151 (2026)

Data-driven high-dimensional statistical inference with generative models

Oz Amram and Manuel Szewc

J. High Energ. Phys. 2025 129 (2025)

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ISSN 2470-0029 (online), 2470-0010 (print).

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