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 | 06019 | |
| Number of page(s) | 9 | |
| Section | Physics Analysis Tools | |
| DOI | https://doi.org/10.1051/epjconf/202429506019 | |
| Published online | 06 May 2024 | |
- K. Aamodt, A.A. Quintana, R. Achenbach, S. Acounis, D. Adamová, C. Adler, M. Aggarwal, F. Agnese, G.A. Rinella, Z. Ahammed et al., Journal of Instrumentation 3, S08002 (2008) [Google Scholar]
- M.I.j. Marian Ivanov, Rootinteractive, https://github.com/miranov25/RootInteractive (2021) [Google Scholar]
- J. Alme et al. (ALICE TPC) (2023), 2304.03881 [Google Scholar]
- M. Arslandok, E. Hellbär, M. Ivanov, R.H. Münzer, J. Wiechula, Particles 5, 84 (2022) [CrossRef] [Google Scholar]
- W. McKinney, Data Structures for Statistical Computing in Python, in Proceedings of the 9th Python in Science Conference, edited by S. van der Walt, J. Millman (2010), pp. 51 – 56 [Google Scholar]
- D. Petersohn, R. Zadeh, M. Zaharia, X. Meng, E. Smith, J.W. Kottalam, R. Liaw, A. Ghodsi, I. Stoica, Modin: Scale your pandas workflows by changing one line of code, https://github.com/modin-project/modin (2019), accessed: 2023-09-04 [Google Scholar]
- D. Piparo, P. Canal, E. Guiraud, X.V. Pla, G. Ganis, G. Amadio, A. Naumann, E. Tejedor, Rdataframe: Easy parallel root analysis at 100 threads, in EPJ Web of Conferences (EDP Sciences, 2019), Vol. 214, p. 06029 [CrossRef] [EDP Sciences] [Google Scholar]
- E. Guiraud, J. Blomer, S. Hageboeck, A. Naumann, V. Padulano, E. Tejedor, S. Wunsch, RDataFrame enhancements for HEP analyses, in Journal of Physics: Conference Series (IOP Publishing, 2023), Vol. 2438, p. 012116 [CrossRef] [Google Scholar]
- J.P. Ianna Osborne, arXiv preprint (2023), 2302.09860 [Google Scholar]
- Bokeh Development Team, Bokeh: Python library for interactive visualization (2018), https://bokeh.pydata.org/en/latest/ [Google Scholar]
- F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg et al., Journal of Machine Learning Research 12, 2825 (2011) [Google Scholar]
- T. Chen, C. Guestrin, XGBoost: A Scalable Tree Boosting System, in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM, New York, NY, USA, 2016), KDD ’16, pp. 785–794, ISBN 978-1-4503-4232-2, 11 [Google Scholar]
- O. Ronneberger, P. Fischer, T. Brox, U-net: Convolutional networks for biomedical image segmentation (2015), 1505.04597, 11 [Google Scholar]
- WebAssembly Core Specification, https://www.w3.org/TR/wasm-core-2/ [Google Scholar]
- O.R. developers, Onnx runtime, https://onnxruntime.ai/ (2021) [Google Scholar]
- S. Athey, J. Tibshirani, S. Wager, The Annals of Statistics 47, 1148 (2019), 1610.01271 [CrossRef] [Google Scholar]
- A.S. Framework, Aliroot, https://github.com/alisw/AliRoot (2021) [Google Scholar]
- J. Alme et al., Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 622, 316 (2010) [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.