Kramer, J., & Lu, T. (2025). A Reproducible Framework for Benchmarking Machine Learning Operations (MLOps) Infrastructures: Comparing Bare-Metal and Orchestrated Machine Learning Workflows. Cureus Journal of Computer Science, 2(1). https://doi.org/10.7759/s44389-025-08693-x
ISO-690 (author-date, English)KRAMER, Julian und LU, Tianxiang, 2025. A Reproducible Framework for Benchmarking Machine Learning Operations (MLOps) Infrastructures: Comparing Bare-Metal and Orchestrated Machine Learning Workflows. Cureus Journal of Computer Science. 1 Dezember 2025. Vol. 2, no. 1, . DOI 10.7759/s44389-025-08693-x.
Modern Language Association 9th editionKramer, J., und T. Lu. „A Reproducible Framework for Benchmarking Machine Learning Operations (MLOps) Infrastructures: Comparing Bare-Metal and Orchestrated Machine Learning Workflows“. Cureus Journal of Computer Science, Bd. 2, Nr. 1, Dezember 2025, https://doi.org/10.7759/s44389-025-08693-x.
Mohr Siebeck - Recht (Deutsch - Österreich)Kramer, Julian/Lu, Tianxiang: A Reproducible Framework for Benchmarking Machine Learning Operations (MLOps) Infrastructures: Comparing Bare-Metal and Orchestrated Machine Learning Workflows, Cureus Journal of Computer Science 2025,
Emerald - HarvardKramer, J. und Lu, T. (2025), „A Reproducible Framework for Benchmarking Machine Learning Operations (MLOps) Infrastructures: Comparing Bare-Metal and Orchestrated Machine Learning Workflows“, Cureus Journal of Computer Science, Vol. 2 No. 1, verfügbar unter:https://doi.org/10.7759/s44389-025-08693-x.