| Learning-based optimisation of particle accelerators under partial observability without real-world training J Kaiser, O Stein, A Eichler International Conference on Machine Learning, 10575-10585, 2022 | 24 | 2022 |
| First steps toward an autonomous accelerator, a common project between DESY and KIT A Eichler, F Burkart, J Kaiser, W Kuropka, O Stein, E Bründermann, ... Proc. IPAC’21, 2182-2185, 2021 | 20 | 2021 |
| Accelerating linear beam dynamics simulations for machine learning applications O Stein, J Kaiser, A Eichler, I Agapov Proceedings of the 13th International Particle Accelerator Conference, 2022 | 8 | 2022 |
| Learning to do or learning while doing: Reinforcement learning and bayesian optimisation for online continuous tuning J Kaiser, C Xu, A Eichler, AS Garcia, O Stein, E Bründermann, W Kuropka, ... arXiv preprint arXiv:2306.03739, 2023 | 7 | 2023 |
| Beam trajectory control with lattice-agnostic reinforcement learning C Xu, E Bründermann, AS Müller, AS Garcia, J Kaiser, A Eichler Proc. IPAC’23, 2023 | 6 | 2023 |
| Bayesian optimization algorithms for accelerator physics R Roussel, AL Edelen, T Boltz, D Kennedy, Z Zhang, X Huang, D Ratner, ... arXiv preprint arXiv:2312.05667, 2023 | 5 | 2023 |
| Machine learning for combined scalar and spectral longitudinal phase space reconstruction J Kaiser, A Eichler, S Tomin, Z Zhu Proc. IPAC’23, 4413-4416, 2023 | 3 | 2023 |
| Designing recurrent neural networks for monitoring embedded devices FH Bahnsen, J Kaiser, G Fey 2021 IEEE European Test Symposium (ETS), 1-4, 2021 | 3 | 2021 |
| Large language models for human-machine collaborative particle accelerator tuning through natural language J Kaiser, A Eichler, A Lauscher arXiv preprint arXiv:2405.08888, 2024 | 2 | 2024 |
| Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations J Kaiser, C Xu, A Eichler, AS Garcia arXiv preprint arXiv:2401.05815, 2024 | 2 | 2024 |
| Bridging the gap between machine learning and particle accelerator physics with high-speed, differentiable simulations J Kaiser, C Xu, A Eichler, A Santamaria Garcia Physical Review Accelerators and Beams 27 (5), 054601, 2024 | 1 | 2024 |
| Undulator linear taper control at the European X-Ray Free-Electron Laser facility S Tomin, J Kaiser, NM Lockmann, T Wohlenberg, I Zagorodnov Physical Review Accelerators and Beams 27 (4), 042801, 2024 | 1 | 2024 |
| Reinforcement learning-trained optimisers and Bayesian optimisation for online particle accelerator tuning J Kaiser, C Xu, A Eichler, A Santamaria Garcia, O Stein, E Bründermann, ... Scientific reports 14 (1), 15733, 2024 | | 2024 |
| TOWARDS FEW-SHOT REINFORCEMENT LEARNING IN PARTICLE ACCELERATOR CONTROL: TOWARDS FEW-SHOT REINFORCEMENT LEARNING IN PARTICLE ACCELERATOR CONTROL S Hirländer, L Lamminger, S Pochaba, J Kaiser, C Xu, AS Garcia, V Kain, ... 15th International Particle Accelerator Conference: 15th International …, 2024 | | 2024 |
| Do We Need Real Data?-Testing and Training Algorithms with Artificial Geolocation Data J Kaiser, K Bavendiek, S Schupp Gesellschaft für Informatik eV, 2019 | | 2019 |
| The reinforcement learning for autonomous accelerators collaboration AS Garcia, L Scomparin, C Xu, S Hirlaender Proc. IPAC'24, 1809-1812, 0 | | |
| TOWARDS FEW-SHOT REINFORCEMENT LEARNING IN PARTICLE ACCELERATOR CONTROL J Kaiser, GC Xu, AS Garcia, L Scomparin | | |
| Do We Need Real Data? Ű Testing and Training Algorithms with ArtiĄcial Geolocation Data J Kaiser, K Bavendiek, S Schupp 50 Jahre Gesellschaft für Informatik, 205, 0 | | |
Annika EichlerDESY在 desy.de 的电子邮件经过验证
