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J. Wan, A. Plastun, and P. Ostroumov, “Machine learning-based non-destructive measurement of bunch length at FRIB”, in Proc. 32nd Linear Accelerator Conf. (LINAC'24), Chicago, IL, USA, Aug. 2024, pp. 335-337. |
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J. Wan, S. Zhao, Y. Hao, W. Chang, and H. Ao, “Machine learning enabled model predictive control for the resonance frequency of the FRIB RFQ”, in Proc. 32nd Linear Accelerator Conf. (LINAC'24), Chicago, IL, USA, Aug. 2024, pp. 338-340. |
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J. Wan, Y. Hao, and J. Qiang, “Machine learning-based symplectic model for space-charge effect simulation”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper WEPS011, this conference. |
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J. Qiang, Y. Hao, and J. Wan, “A module for fast auto differentiable simulations”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper WEBN2, this conference. |
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J. Wan, W. Chang, Y. Hao, and S. Zhao, “Machine learning-based model predictive control of the FRIB SRF”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THPM011, this conference. |
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Y. Jiao and J. Wan, “Machine learning application studies in lattice design and optimization of 4th generation synchrotron radiation light source”, presented at the 14th Symposium on Accelerator Physics (SAP'23), Xichang, China, Jul. 2023, paper WEAA03, unpublished. |
