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For Word

[n]	F. Basbous, F. Haddad, D. Mateus, and F. Poirier, “Transfer Learning for Generalizing a Hybrid Autoencoder-Isolation Forest Model for Time Series Anomaly Detection in ARRONAX Cyclotron Operational Data”, presented at the IPAC'26, Deauville, France, May 2026, paper SUP6001, this conference.

For LaTeX

%\cite{Basbous:IPAC26-SUP6001} \bibitem{Basbous:IPAC26-SUP6001} F. Basbous, F. Haddad, D. Mateus, and F. Poirier, \textquotedblleft{Transfer Learning for Generalizing a Hybrid Autoencoder-Isolation Forest Model for Time Series Anomaly Detection in ARRONAX Cyclotron Operational Data}\textquotedblright, presented at the IPAC’26, Deauville, France, May 2026, paper SUP6001, this conference.

For BibTeX

@conference{basbous:ipac26-sup6001, author = {F. Basbous and F. Haddad and D. Mateus and F. Poirier}, title = {{Transfer Learning for Generalizing a Hybrid Autoencoder-Isolation Forest Model for Time Series Anomaly Detection in ARRONAX Cyclotron Operational Data}}, pages = {}, paper = {SUP6001}, intype = {presented at the}, series = {International Particle Accelerator Conference}, publisher = {JACoW Publishing, Geneva, Switzerland}, note = {presented at IPAC'26, Deauville, France, May 2026, paper SUP6001, this conference}, language = {english} }

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Metadata

Paper Title: Transfer Learning for Generalizing a Hybrid Autoencoder-Isolation Forest Model for Time Series Anomaly Detection in ARRONAX Cyclotron Operational Data
Conference: 17th Int. Particle Accelerator Conf. (IPAC'26)
Paper ID: SUP6001
Original Author String: F. Basbous, F. Haddad, D. Mateus, F. Poirier

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