Open Access
Issue
EPJ Web Conf.
Volume 320, 2025
20th International Conference on Calorimetry in Particle Physics (CALOR 2024)
Article Number 00025
Number of page(s) 4
DOI https://doi.org/10.1051/epjconf/202532000025
Published online 07 March 2025
  1. R. Wigmans. Calorimetry. Oxford Science Publications, 2000. [Google Scholar]
  2. M. A.Thomson, Particle Flow Calorimetry and the PandoraPFA Algorithm. NIM A 611, 25–40 (2009). [Google Scholar]
  3. D. Shaked-Renous et al., Test-beam and simulation studies towards RPWELL-based DHCAL. JINST 17, P12008 (2020). [Google Scholar]
  4. CALICE Collaboration, Analysis of Testbeam Data of the Highly Granular RPC-Steel CALICE Digital Hadron Calorimeter and Validation of Geant4 Monte Carlo Models. NIM A 939, 89–105(2019). [Google Scholar]
  5. S. Agostinelli et al., GEANT4: A Simulation toolkit. NIM A506, 250 (2003). [CrossRef] [Google Scholar]
  6. M. Zaheer et al., Deep Sets. arXiv:1703.06114 (2018). [Google Scholar]
  7. A. Vaswani et al., Attention Is All You Need. arXiv:1706.03762 (2023). [Google Scholar]
  8. A. Paszke et. al., Automatic differentiation in Py-Torch. NIPS 2017 Workshop Autodiff, October 2017. [Google Scholar]
  9. M. Abadi et al., Tensorflow: A system for large-scale machine learning, doi.org/10.5281/zenodo.5043456, 2016. [Google Scholar]
  10. Y. LeCun, L. Bottou, G.B. Orr and K.-R. Müller, Efficient backprop, in Neural networks: Tricks of the trade, pp. 9–50, Springer (2002) [Google Scholar]

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