Machine learning for design optimization of storage ring nonlinear dynamics. - Faya Wang; Minghao Song; Auralee Edelen; Xiaobiao Huang (CoRR, 2019)

Online tuning and light source control using a physics-informed Gaussian process Adi. - Adi Hanuka; Joseph Duris; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; Daniel Ratner; Xiaobiao Huang (CoRR, 2019)

Physics-informed Gaussian Process for Online Optimization of Particle Accelerators. - Adi Hanuka; Xiaobiao Huang; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; V. R. Lalchand; Daniel Ratner; Joseph Duris (CoRR, 2020)

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II. - Claudio Emma; Auralee Edelen; Adi Hanuka; Brendan O'Shea; Alexander Scheinker (Inf., 2021)

Improving surrogate model accuracy for the LCLS-II injector frontend using convolutional neural networks and transfer learning. - Lipi Gupta; Auralee Edelen; Nicole Neveu; Aashwin Mishra; Christopher Mayes; Youngkee Kim (Mach. Learn. Sci. Technol., 2021)

Neural Network Solver for Coherent Synchrotron Radiation Wakefield Calculations in Accelerator-based Charged Particle Beams. - Auralee Edelen; Christopher Mayes (CoRR, 2022)

Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements. - Sara A. Miskovich; Willie Neiswanger; William Colocho; Claudio Emma; Jacqueline Garrahan; Timothy Maxwell; Christopher Mayes; Stefano Ermon; Auralee Edelen; Daniel Ratner (CoRR, 2022)

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives. - Sara A. Miskovich; Willie Neiswanger; William Colocho; Claudio Emma; Jacqueline Garrahan; Timothy Maxwell; Christopher Mayes; Stefano Ermon; Auralee Edelen; Daniel Ratner (Mach. Learn. Sci. Technol., 2024)

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators. - Kishansingh Rajput; Malachi Schram; Auralee Edelen; Jonathan Colen; Armen Kasparian; Ryan Roussel; Adam Carpenter; He Zhang; Jay Benesch (Mach. Learn. Sci. Technol., 2025)

Outlook Towards Deployable Continual Learning for Particle Accelerators. - Kishansingh Rajput; Sen Lin; Auralee Edelen; Willem Blokland; Malachi Schram (CoRR, 2025)

A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE. - Aashwin Mishra; Matt Seaberg; Ryan Roussel; Frédéric Poitevin; Jana Thayer; Daniel Ratner; Auralee Edelen; Apurva Mehta (CoRR, 2025)