| Phase space reconstruction from accelerator beam measurements using neural networks and differentiable simulations R Roussel, A Edelen, C Mayes, D Ratner, JP Gonzalez-Aguilera, S Kim, ... Physical Review Letters 130 (14), 145001, 2023 | 38 | 2023 |
| Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning R Roussel, JP Gonzalez-Aguilera, YK Kim, E Wisniewski, W Liu, P Piot, ... Nature Communications 12 (1), 1-7, 2021 | 29 | 2021 |
| Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis R Roussel, A Edelen, D Ratner, K Dubey, JP Gonzalez-Aguilera, YK Kim, ... Physical Review Letters 128 (20), 204801, 2022 | 25 | 2022 |
| Towards fully differentiable accelerator modeling J Gonzalez-Aguilera, Y Kim, R Roussel, A Edelen, C Mayes Proc. IPAC'23, 1725-1729, 2023 | 9 | 2023 |
| Efficient six-dimensional phase space reconstructions from experimental measurements using generative machine learning R Roussel, JP Gonzalez-Aguilera, E Wisniewski, A Ody, W Liu, J Power, ... Physical Review Accelerators and Beams 27 (9), 094601, 2024 | 5* | 2024 |
| Four-dimensional phase-space reconstruction of flat and magnetized beams using neural networks and differentiable simulations S Kim, JP Gonzalez-Aguilera, P Piot, G Chen, S Doran, YK Kim, W Liu, ... Physical Review Accelerators and Beams 27 (7), 074601, 2024 | 3 | 2024 |
| Advancements in backwards differentiable beam dynamics simulations for accelerator design, model calibration, and machine learning R Roussel, G Charleux, A Edelen, A Eichler, J Gonzalez-Aguilera, ... Proc. LINAC2024, 694-697, 2024 | | 2024 |
| Detailed characterization of coherent synchrotron radiation effects using generative phase space reconstruction J Gonzalez-Aguilera, Y Kim, R Roussel, A Edelen Proc. IPAC'24, 2442-2445, 2024 | | 2024 |
| Progress on combining digital twins and machine learning-based control for accelerators at SLAC AL Edelen, R Roussel, E Cropp, C Emma, C Mayes, D Ratner, J Bellister, ... Proc. IPAC'24, 1846-1849, 2024 | | 2024 |
| Bayesian Techniques for Accelerator Characterization and Control RJ Roussel, AL Edelen, JP Gonzalez-Aguilera, YK Kim, CE Mayes SLAC National Accelerator Lab., Menlo Park, CA (United States), 2022 | | 2022 |
| Bayesian active learning for autonomous parameter space exploration in particle accelerators JP Gonzalez-Aguilera, R Roussel, YK Kim APS April Meeting Abstracts 2022, F01. 054, 2022 | | 2022 |
| Beam Diagnostics for Multi-Objective Bayesian Optimization at the Argonne Wakefield Accelerator Facility JP Gonzalez-Aguilera, R Roussel, YK Kim, W Liu, P Piot, JG Power, ... Proc. IPAC'21, 960-962, 2021 | | 2021 |
| Novel Accelerator Diagnostic Development for Multi-Objective Bayesian Optimization at the Argonne Wakefield Accelerator Facility JP Gonzalez Aguilera, R Roussel, YK Kim APS April Meeting Abstracts 2021, E15. 008, 2021 | | 2021 |
| Implementación de algoritmos de aprendizaje supervisado en la búsqueda de estrellas variables JP González Aguilera Universidad de los Andes, 2019 | | 2019 |
Ryan RousselSLAC National Accelerator Laboratory在 slac.stanford.edu 的电子邮件经过验证
