| Coherent soft X-ray pulses from an echo-enabled harmonic generation free-electron laser P Rebernik Ribič, A Abrami, L Badano, M Bossi, HH Braun, N Bruchon, ... Nature Photonics 13 (8), 555-561, 2019 | 188 | 2019 |
| Sample-efficient reinforcement learning for CERN accelerator control V Kain, S Hirlander, B Goddard, FM Velotti, GZ Della Porta, N Bruchon, ... Physical Review Accelerators and Beams 23 (12), 124801, 2020 | 107 | 2020 |
| Basic reinforcement learning techniques to control the intensity of a seeded free-electron laser N Bruchon, G Fenu, G Gaio, M Lonza, FH O’Shea, FA Pellegrino, ... Electronics 9 (5), 781, 2020 | 57 | 2020 |
| Model-free and Bayesian ensembling model-based deep reinforcement learning for particle accelerator control demonstrated on the Fermi FEL S Hirlaender, N Bruchon arXiv preprint arXiv:2012.09737, 2020 | 37 | 2020 |
| Policy gradient methods for free-electron laser and terahertz source optimization and stabilization at the FERMI free-electron laser at Elettra FH O’Shea, N Bruchon, G Gaio Physical Review Accelerators and Beams 23 (12), 122802, 2020 | 34 | 2020 |
| Toward the application of reinforcement learning to the intensity control of a seeded free-electron laser N Bruchon, G Fenu, G Gaio, M Lonza, FA Pellegrino, E Salvato 2019 23rd International Conference on Mechatronics Technology (ICMT), 1-6, 2019 | 17 | 2019 |
| Free-electron laser spectrum evaluation and automatic optimization N Bruchon, G Fenu, G Gaio, M Lonza, FA Pellegrino, L Saule Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2017 | 17 | 2017 |
| JACOW: Beam Performance with the LHC Injectors Upgrade L Sito, J Coupard, K Hanke, R Wegner, E Shaposhnikova, D Quartullo, ... JACoW HB 2023, 1-8, 2024 | 12 | 2024 |
| Linear optics control of sideband instability for improved free-electron laser spectral brightness G Perosa, EM Allaria, L Badano, N Bruchon, P Cinquegrana, ... Physical Review Accelerators and Beams 23 (11), 110703, 2020 | 12 | 2020 |
| Spectrotemporal control of soft x-ray laser pulses NS Mirian, E Allaria, N Bruchon, P Cinquegrana, MB Danailov, ... Physical Review Accelerators and Beams 23 (6), 060701, 2020 | 12 | 2020 |
| Advances in automatic performance optimization at FERMI G Gaio, M Lonza, N Bruchon, L Saule Proceedings of the 16th International Conference on Accelerator & Large …, 2017 | 10 | 2017 |
| An online iterative linear quadratic approach for a satisfactory working point attainment at FERMI N Bruchon, G Fenu, G Gaio, S Hirlander, M Lonza, FA Pellegrino, ... Information 12 (7), 262, 2021 | 6 | 2021 |
| Test of Machine Learning at the CERN LINAC4 V Kain, N Bruchon, S Hirlander, N Madysa, I Vojskovic, P Skowronski, ... JACoW Publishing, 2021 | 4 | 2021 |
| Free-electron laser optimization with reinforcement learning N Bruchon, G Fenu, G Gaio, M Lonza, FA Pellegrino, E Salvato 17th Int. Conf. on Acc. and Large Exp. Physics Control Systems, ICALEPCS2019, 2019 | 4 | 2019 |
| Continuous data-driven control of the GTS-LHC ion source at CERN V Kain, N Bruchon, S Hirlaender, D Küchler, BR Mateos, M Schenk Proc. eCRIS 24, 1, 2024 | 2 | 2024 |
| JACOW: Operational Tool for Automatic Setup of Controlled Longitudinal Emittance Blow-Up in the CERN SPS N Bruchon, G Papotti, I Karpov, N Madysa, D Quartullo JACoW ICALEPCS 2023, TUPDP086, 2023 | 2 | 2023 |
| Feasibility Investigation on Several Reinforcement Learning Techniques to Improve the Performance of the FERMI Free-Electron Laser N Bruchon Università degli Studi di Trieste, 2021 | 2 | 2021 |
| First lasing of a free electron laser in the soft x-ray spectral range with echo enabled harmonic generation E Allaria, A Abrami, L Badano, M Bossi, N Bruchon, F Capotondi, ... FEL2019: Proceedings of the 39th International Free-Electron Laser …, 2019 | 2 | 2019 |
| Impedance and thermal studies of the CERN SPS wire scanners and mitigation of wire heating E de la Fuente, I Papazoglou, L Sito, W Andreazza, C Antuono, ... 15th Int. Particle Accelerator Conf.(IPAC’24), paper WEPG29, 0 | 2 | |
| TRAJECTORY STEERING FOR DC BEAMS AT THE CERN SPS USING REINFORCEMENT LEARNING BASED ON INTENSITY MEASUREMENTS AM de Oñate, N Bruchon, V Kain, M Schenk, BR Mateos | 2 | |
