@InProceedings{mukhtar_et_al:OASIcs.DX.2024.14,
  author =	{Mukhtar, Adil and Hirsch, Thomas and Schweiger, Gerald},
  title =	{{One-Class Classification and Cluster Ensembles for Anomaly Detection and Diagnosis in Multivariate Time Series Data}},
  booktitle =	{35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)},
  pages =	{14:1--14:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-356-0},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{125},
  editor =	{Pill, Ingo and Natan, Avraham and Wotawa, Franz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2024.14},
  URN =		{urn:nbn:de:0030-drops-221064},
  doi =		{10.4230/OASIcs.DX.2024.14},
  annote =	{Keywords: Anomaly Detection and Diagnosis, Machine Learning, Explainable AI, One-class Classification}
}