Article references

Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Training and Serving ML workloads with Kubeflow at CERN

Dejan Golubovic, Ricardo Rocha

EPJ Web Conf., 251 (2021) 02067

Published online: 2021-08-23

DOI: https://doi.org/10.1051/epjconf/202125102067

This article has been cited by the following article(s):

Developments on the “Machine Learning as a Service for High Energy Physics” Framework and Related Cloud Native Solution

Luca Giommi, Daniele Spiga, Mattia Paladino, Valentin Kuznetsov and Daniele Bonacorsi
IEEE Transactions on Cloud Computing 13 (1) 429 (2025)
https://doi.org/10.1109/TCC.2025.3535793

Anupama Babu, Athiramol S, Sheenamol Yousaf and Sudheep Elayidom M
1 (2025)
https://doi.org/10.1109/ICMCTC62214.2025.11196190

A supervised AI-based toolchain for anomaly detection, diagnosis, and reconfiguration for the life-support system of the COLUMBUS module of the ISS

Mark Tappe, Lukas Moddemann, Henrik Steude, Nemanja Hranisavljevic, Alexander Diedrich, Stephan Myschik, Christian Geier, Martin Creutzenberg, Philipp Grashorn, Tobias Hoppe, Hauke Ernst and Oliver Niggemann
CEAS Space Journal (2025)
https://doi.org/10.1007/s12567-025-00654-3

Unlabeled learning algorithms and operations: overview and future trends in defense sector

Eduardo e Oliveira, Marco Rodrigues, João Paulo Pereira, António M. Lopes, Ivana Ilic Mestric and Sandro Bjelogrlic
Artificial Intelligence Review 57 (3) (2024)
https://doi.org/10.1007/s10462-023-10692-0

Aitor Arjona, Bernard Metzler and Pascal Spörri
1 (2024)
https://doi.org/10.1109/ICNP61940.2024.10858528

Distributed Machine Learning Workflow with PanDA and iDDS in LHC ATLAS

Wen Guan, Tadashi Maeno, Rui Zhang, Christian Weber, Torre Wenaus, Aleksandr Alekseev, Fernando Harald Barreiro Megino, Kaushik De, Edward Karavakis, Alexei Klimentov, Tatiana Korchuganova, FaHui Lin, Paul Nilsson, Zhaoyu Yang, Xin Zhao, R. De Vita, X. Espinal, P. Laycock and O. Shadura
EPJ Web of Conferences 295 04019 (2024)
https://doi.org/10.1051/epjconf/202429504019

Jean Pierre Soto-Chirinos, Henry Ivan Condori-Alejo and Guina Sotomayor Alzamora
1 (2023)
https://doi.org/10.1109/INTERCON59652.2023.10326073

Jet Energy Calibration with Deep Learning as a Kubeflow Pipeline

Daniel Holmberg, Dejan Golubovic and Henning Kirschenmann
Computing and Software for Big Science 7 (1) (2023)
https://doi.org/10.1007/s41781-023-00103-y

Seamless Transition From Machine Learning on the Cloud to Industrial Edge Devices With Thinger.io

Alvaro Luis Bustamante, Miguel A. Patricio, Antonio Berlanga and José M. Molina
IEEE Internet of Things Journal 10 (18) 16548 (2023)
https://doi.org/10.1109/JIOT.2023.3268771

Alexandre Carqueja, Bruno Cabral, Joao Paulo Fernandes and Nuno Lourenco
455 (2022)
https://doi.org/10.1109/SSCI51031.2022.10022107

Theodoros Tsourdinis, Ilias Chatzistefanidis, Nikos Makris and Thanasis Korakis
1 (2022)
https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798391