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C. Leon, A. Scheinker, and A. Bormanis, “Solving the Orszag-Tang vortex magnetohydrodynamics problem with physics-constrained convolutional neural networks”, in Proc. 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper MOPS72, pp. 897-900. |
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C. Leon, A. Scheinker, N. Yampolsky, and P. Anisimov, “Utilizing neural networks to speed up coherent synchrotron radiation computations”, in Proc. 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper MOPS73, pp. 901-904. |
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C. Leon, A. Scheinker, N. Yampolsky, and P. Anisimov, “Generalization ability of convolutional neural networks trained for coherent synchrotron radiation computations”, in Proc. 32nd Linear Accelerator Conf. (LINAC'24), Chicago, IL, USA, Aug. 2024, pp. 219-222. |
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C. Leon, E.-C. Huang, A. Scheinker, and P. M. Anisimov, “Integrating simulation and machine learning for Proton Storage Ring beam analysis”, in Proc. 6th North American Particle Accelerator Conference (NAPAC'25), Sacramento, California, USA, Aug. 2025, pp. 196-199. |
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C. Leon, A. Scheinker, N. Yampolsky, and P. M. Anisimov, “Machine learning-driven computations of 3D Coherent Synchrotron Radiation”, in Proc. 6th North American Particle Accelerator Conference (NAPAC'25), Sacramento, California, USA, Aug. 2025, pp. 279-283. |
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C. Leon, P. M. Anisimov, and A. Scheinker, “Machine Learning-Assisted Calibration of The Accelerator Simulator HPSim”, presented at the 17th Int. Particle Accelerator Conf. (IPAC'26), Deauville, France, May 2026, paper MOP6320, this conference. |
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M. Kay, P. M. Anisimov, and C. Leon, “APPLYING MACHINE LEARNING TO LONGITUDINAL PHASE SPACE RECONSTRUCTION IN THE LANSCE CCL”, presented at the 17th Int. Particle Accelerator Conf. (IPAC'26), Deauville, France, May 2026, paper WEP4315, this conference. |
