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[n]	S. Kuroguchi et al., “Harnessing machine learning for the optimal design of ILC e-driven positron source”, in Proc. IPAC'24, Nashville, TN, USA, May 2024, pp. 886-888. doi:10.18429/JACoW-IPAC2024-MOPS69
[n]	A. Scheinker, “Adaptive Control and Machine Learning for Particle Accelerator Beam Control and Diagnostics”, in Proc. IBIC'21, Pohang, Korea, Sep. 2021, pp. 466-472. doi:10.18429/JACoW-IBIC2021-THOB03
[n]	Y. Liang et al., “Multi-bunch operation mode for simultaneously serving SASE and seeding FEL beamlines”, presented at the IPAC'23, Venice, Italy, May 2023, paper TUPL047, unpublished. 
[n]	V. Derenchuk, R. Brown, P. Schwandt, M. Wedekind, J. Hicks, and D. Friesel, “The IUCF High Intensity Polarized Ion Source Project”, in Proc. PAC'93, Washington D.C., USA, Mar. 1993, pp. 3184-3187. 
[n]	J-M. Lagniel, “Linac Architecture for High Power Proton Sources”, in Proc. LINAC'00, Monterey, CA, USA, Aug. 2000, paper FR103, pp. 1028-1032. 
[n]	I. Lobach, M. Borland, K. C. Harkay, N. Kuklev, A. Sannibale, and Y. Sun, “Machine Learning for Anomaly Detection and Classification in Particle Accelerators”, in Proc. NAPAC'22, Albuquerque, NM, USA, Aug. 2022, pp. 311-314. doi:10.18429/JACoW-NAPAC2022-TUYE4
[n]	J. Chen, S. Cao, L. Lai, Y. Leng, R. Yuan, and R. Jiang, “Optimization and development of the CBPM system for the SHINE”, in Proc. IPAC'23, Venice, Italy, May 2023, pp. 4876-4878. doi:10.18429/JACoW-IPAC2023-THPL183

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