SALLES, Rebecca, LANGE, Benoit, AKBARINIA, Reza, MASSEGLIA, Florent, OGASAWARA, Eduardo und PACITTI, Esther, 2025. Scalable and accurate online multivariate anomaly detection. Information Systems. 1 Juni 2025. Vol. 131, , p. N.PAG-0. DOI 10.1016/j.is.2025.102524.
Elsevier - Harvard (with titles)Salles, R., Lange, B., Akbarinia, R., Masseglia, F., Ogasawara, E., Pacitti, E., 2025. Scalable and accurate online multivariate anomaly detection. Information Systems 131, N.PAG-0. https://doi.org/10.1016/j.is.2025.102524
American Psychological Association 7th editionSalles, R., Lange, B., Akbarinia, R., Masseglia, F., Ogasawara, E., & Pacitti, E. (2025). Scalable and accurate online multivariate anomaly detection. Information Systems, 131, N.PAG-0. https://doi.org/10.1016/j.is.2025.102524
Springer - Basic (author-date)Salles R, Lange B, Akbarinia R, Masseglia F, Ogasawara E, Pacitti E (2025) Scalable and accurate online multivariate anomaly detection.. Information Systems 131:N.PAG-0. https://doi.org/10.1016/j.is.2025.102524
Juristische Zitierweise (Stüber) (Deutsch)Salles, Rebecca/ Lange, Benoit/ Akbarinia, Reza/ Masseglia, Florent/ Ogasawara, Eduardo/ Pacitti, Esther, Scalable and accurate online multivariate anomaly detection., Information Systems 2025, N.PAG-0.