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Physical Review D

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Eur. Phys. J. C (1)Phys. Rev. C (1)

Articles Citing

Machine learning assisted unfolding for neutrino cross-section measurements with the OmniFold technique

R. G. Huang ¹, A. Cudd ², M. Kawaue ³, T. Kikawa ³, B. Nachman ¹, V. Mikuni ¹, and C. Wilkinson ¹

¹Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
²University of Colorado Boulder, Boulder, Colorado 80309, USA
³Kyoto University, Department of Physics, Kyoto, Japan

A practical guide to unbinned unfolding

Florencia Canelli, Kyle Cormier, Andrew Cudd, Dag Gillberg, Roger G. Huang, Weijie Jin, Sookhyun Lee, Vinicius Mikuni, Laura Miller, Benjamin Nachman, Jingjing Pan, Tanmay Pani, Mariel Pettee, Youqi Song, and Fernando Torales Acosta

Eur. Phys. J. C 86 106 (2026)

Re-optimization of a deep neural network model for electron-carbon scattering using new experimental data

Beata E. Kowal, Krzysztof M. Graczyk, Artur M. Ankowski, Rwik Dharmapal Banerjee, Jose L. Bonilla, Hemant Prasad, and Jan T. Sobczyk

Phys. Rev. C 112 055504 (2025)

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