Open Access
Issue
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
Article Number 09024
Number of page(s) 6
Section Artificial Intelligence and Machine Learning
DOI https://doi.org/10.1051/epjconf/202429509024
Published online 06 May 2024
  1. S.L. Glashow, J. Iliopoulos, L. Maiani, Phys. Rev. D 2 (1970) [Google Scholar]
  2. R. Aaij et al., Journal of High Energy Physics 2017, 55 (2017) [CrossRef] [Google Scholar]
  3. S. Wehle et al. (Belle Collaboration), Phys. Rev. Lett. 126, 161801 (2021) [CrossRef] [PubMed] [Google Scholar]
  4. A. Sibidanov et al., Detecting lepton universality violation in angular distributions of B → K∗ℓ+ decays (2022), 2203.06827 [Google Scholar]
  5. K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition (2015), 1512.03385 [Google Scholar]
  6. A. Geron, Hands-on machine learning with scikit-learn, keras, and TensorFlow, 2nd edn. (O’Reilly Media, Sebastopol, CA, 2019) [Google Scholar]
  7. M.D. Schwartz, Quantum Field Theory and the standard model (Cambridge University Press, 2013) [CrossRef] [Google Scholar]
  8. HEP ML Community, A Living Review of Machine Learning for Particle Physics, and references therein, https://iml-wg.github.io/HEPML-LivingReview/ [Google Scholar]
  9. D.J. Lange, Nucl. Instrum. Meth. A 462, 152 (2001) [Google Scholar]
  10. W. Altmannshofer, P. Stangl, The European Physical Journal C 81, 952 (2021) [CrossRef] [PubMed] [Google Scholar]
  11. M. Abadi et al., TensorFlow: Large-scale machine learning on heterogeneous systems (2015), software available from tensorflow.org, https://www.tensorflow.org/ [Google Scholar]
  12. F. Chollet et al., Keras, https://keras.io (2015) [Google Scholar]
  13. B. Bhattacharya et al., Phys. Rev. D 107, 015011 (2023) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.