|
R. Roussel et al., “Advancements in backwards differentiable beam dynamics simulations for accelerator design, model calibration, and machine learning”, in Proc. 32nd Linear Accelerator Conf. (LINAC'24), Chicago, IL, USA, Aug. 2024, pp. 768-771. |
|
C. Xu et al., “Updates to the differentiable accelerator simulation code Cheetah”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper WEPS034, this conference. |
|
Y. Sun et al., “Machine learning for calibration drift forecasting in superconducting RF cavities”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THPS135, this conference. |
|
A. Eichler et al., “Enhancing quench detection in SRF cavities at the EuXFEL: Towards machine learning approaches and practical challenges”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THPS134, this conference. |
|
C. Xu et al., “Efficient data-driven model predictive control for online accelerator tuning”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THPM116, this conference. |
|
A. Santamaria Garcia, A. Eichler, S. Hirlaender, J. Kaiser, and C. Xu, “Reinforcement learning in particle accelerators”, presented at the 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THYD1, this conference. |
