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Author: N. Urban


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Reference
W. Lin et al., “AGS Booster model calibration and digital-twin development”, in Proc. 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper THPG78, pp. 3449-3452.
W. Lin, C. Kelly, G. Hoffstaetter, K. Brown, and N. Urban, “Machine learning assisted Bayesian calibration of accelerator digital twin from orbit response data”, in Proc. 6th North American Particle Accelerator Conference (NAPAC'25), Sacramento, California, USA, Aug. 2025, pp. 177-181.
W. Lin et al., “Machine-Learning–Assisted Bayesian Uncertainty Quantification for Accelerator Digital Twin Modeling and Control”, presented at the 17th Int. Particle Accelerator Conf. (IPAC'26), Deauville, France, May 2026, paper MOP6310, this conference.
T. Hellert et al., “Agentic AI as a Middle Layer for Accelerator Control: Multi-Facility Deployment and Early Results”, presented at the 17th Int. Particle Accelerator Conf. (IPAC'26), Deauville, France, May 2026, paper MOP6324, this conference.
J.-L. Vay et al., “Overview of the US DOE Multi-Office particle Accelerator Team (MOAT) project”, presented at the 17th Int. Particle Accelerator Conf. (IPAC'26), Deauville, France, May 2026, paper MOV6302, this conference.


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