STEGEMAN, ROY
STEGEMAN, ROY
Dipartimento di Fisica Aldo Pontremoli
The path to $$\hbox {N}^3\hbox {LO}$$ parton distributions [The path to N3 LO parton distributions]
2024 R.D. Ball, A. Barontini, A. Candido, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, F. Hekhorn, Z. Kassabov, N. Laurenti, G. Magni, E.R. Nocera, T.R. Rabemananjara, J. Rojo, C. Schwan, R. Stegeman, M. Ubiali
Determination of the theory uncertainties from missing higher orders on NNLO parton distributions with percent accuracy
2024 R.D. Ball, A. Barontini, A. Candido, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, F. Hekhorn, Z. Kassabov, N. Laurenti, G. Magni, E.R. Nocera, T.R. Rabemananjara, J. Rojo, C. Schwan, R. Stegeman, M. Ubiali
Photons in the proton: implications for the LHC
2024 R.D. Ball, A. Barontini, A. Candido, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, F. Hekhorn, Z. Kassabov, N. Laurenti, G. Magni, E.R. Nocera, T.R. Rabemananjara, J. Rojo, C. Schwan, R. Stegeman, M. Ubiali
Determination of the theory uncertainties from missing higher orders on NNLO parton distributions with percent accuracy
2024 R.D. Ball, A. Barontini, A. Candido, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, F. Hekhorn, Z. Kassabov, N. Laurenti, G. Magni, E.R. Nocera, T.R. Rabemananjara, J. Rojo, C. Schwan, R. Stegeman, M. Ubiali
NNPDF/nnpdf
2023 Z. Kassabov, J.M. Cruz-Martinez, S. Carrazza, R. Pearson, C. Voisey, N. Hartland, R. Stegeman, Lucarottoli, R. Abdul Khalek, E. Slade, E.R. Nocera, A. Barontini, S. Tgiani, J. Mariaubiali, Ldd69, A. Candido, D. Kalinkin, Gstagnit, J. Moore, M. Nestor Costantini, S. Voltan
Machine learning and LHC event generation
2023 A. Butter, T. Plehn, S. Schumann, S. Badger, S. Caron, K. Cranmer, F. Armando Di Bello, E. Dreyer, S. Forte, S. Ganguly, D. Gon??alves, E. Gross, T. Heimel, G. Heinrich, L. Heinrich, A. Held, S. H??che, J.N. Howard, P. Ilten, J. Isaacson, T. Jan??en, S. Jones, M. Kado, M. Kagan, G. Kasieczka, F. Kling, S. Kraml, C. Krause, F. Krauss, K. Kr??ninger, R. Kumar Barman, M. Luchmann, V. Magerya, D. Maitre, B. Malaescu, F. Maltoni, T. Martini, O. Mattelaer, B. Nachman, S. Pitz, J. Rojo, M. Schwartz, D. Shih, F. Siegert, R. Stegeman, B. Stienen, J. Thaler, R. Verheyen, D. Whiteson, R. Winterhalder, J. Zupan
STATISTICAL LEARNING FOR STANDARD MODEL PHENOMENOLOGY
2022 R. Stegeman
The path to proton structure at 1% accuracy
2022 R.D. Ball, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, S. Iranipour, Z. Kassabov, J.I. Latorre, E.R. Nocera, R.L. Pearson, J. Rojo, R. Stegeman, C. Schwan, M. Ubiali, C. Voisey, M. Wilson
A data-based parametrization of parton distribution functions
2022 S. Carrazza, C. Juan, R. Stegeman
Studying the parton content of the proton with deep learning models
2021 C. Juan, S. Carrazza, R. Stegeman
Correlation and combination of sets of parton distributions
2021 R.D. Ball, S. Forte, R. Stegeman
An open-source machine learning framework for global analyses of parton distributions
2021 R.D. Ball, S. Carrazza, J. Cruz-Martinez, L. Del Debbio, S. Forte, T. Giani, S. Iranipour, Z. Kassabov, J.I. Latorre, E.R. Nocera, R.L. Pearson, J. Rojo, R. Stegeman, C. Schwan, M. Ubiali, C. Voisey, M. Wilson
N3PDF/evolutionary_keras: Evolutionary Keras 2.1
2020 R. Stegeman, C. Juan, S. Carrazza