Open Access
| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01120 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjconf/202533701120 | |
| Published online | 07 October 2025 | |
- J. Zhu, Y. Xia, L. Wu, D. He, T. Qin, W. Zhou, H. Li, T. Liu, Incorporating BERT into Neural Machine Translation, CoRR abs/2002.06823 (2020), 2002.06823. [Google Scholar]
- A. Borghesi, A. Bartolini, M. Lombardi, M. Milano, L. Benini, Anomaly detection using autoencoders in high performance computing systems, in Proceedings of the AAAI Conference on artificial intelligence (2019), Vol. 33, pp. 9428–9433 [Google Scholar]
- M. Molan, A. Borghesi, D. Cesarini, L. Benini, A. Bartolini, RUAD: Unsupervised anomaly detection in HPC systems, Future Generation Computer Systems 141, 542 (2023). https://doi.org/10.1016/j.future.2022.12.001 [Google Scholar]
- M. Molan, J. Ahmed Khan, A. Borghesi, A. Bartolini, Graph Neural Networks for Anomaly Anticipation in HPC Systems, in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (Association for Computing Machinery, New York, NY, USA, 2023), ICPE ’23 Companion, p. 239–244, ISBN 9798400700729, https://doi.org/10.1145/3578245.3585335 [Google Scholar]
- B. Rabenstein, J. Volz, Prometheus: A Next-Generation Monitoring System (Talk) (USENIX Association, Dublin, 2015) [Google Scholar]
- M. Jones, P. Hurck, W. Phelps, C.W. Salgado, PyPWA: A software toolkit for parameter optimization and amplitude analysis, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 1062, 169150 (2024). https://doi.org/10.1016/j.nima.2024.169150 [Google Scholar]
- P. Welch, The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms, IEEE Transactions on Audio and Electroacoustics 15, 70 (1967). 10.1109/TAU.1967.1161901 [CrossRef] [Google Scholar]
- K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016) [Google Scholar]
- T.K. Rusch, M.M. Bronstein, S. Mishra, A Survey on Oversmoothing in Graph Neural Networks (2023), 2303.10993, https://arxiv.org/abs/2303.10993 [Google Scholar]
- D. McSpadden, M. Jones, A.H. Mohammed, B. Hess, M. Schram, Establishing MLOps for Continual Learning in Computing Clusters, IEEE Software pp. 1–8 (2024). 10.1109/MS.2024.3424256 [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.