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Author: N. Kuklev


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Reference
N. Kuklev, J. Eldred, and M. Balcewicz, “Fermilab Booster beam loss modelling and rebalancing using Bayesian methods”, in Proc. 6th North American Particle Accelerator Conference (NAPAC'25), Sacramento, California, USA, Aug. 2025, pp. 906-910.
R. Roussel, D. Kennedy, A. Edelen, N. Kuklev, S. Miskovich, and Z. Zhang, “Xopt and Badger: a machine learning ecosystem for real-time accelerator control and optimization”, presented at the 20th International Conference on Accelerator and Large Experimental Control Systems (ICALEPCS'25), Chicago, IL, USA, Sep. 2025, paper WEPD086, unpublished.
N. Kuklev, A. Romanov, J. Jarvis, M. Wallbank, and N. Banerjee, “APOLLO: a facility-scale differentiable virtual accelerator at Fermilab FAST/IOTA”, in Proc. 20th International Conference on Accelerator and Large Experimental Control Systems (ICALEPCS'25), Chicago, IL, USA, Sep. 2025, pp. 1249-1253.
R. Roussel, D. Kennedy, A. Edelen, N. Kuklev, S. Miskovich, and Z. Zhang, “Xopt and Badger: a machine learning ecosystem for real-time accelerator control and optimization”, in Proc. 20th International Conference on Accelerator and Large Experimental Control Systems (ICALEPCS'25), Chicago, IL, USA, Sep. 2025, pp. 1271-1275.


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