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Jan Kaiser
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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
192021
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
172022
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
52023
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
52022
Designing recurrent neural networks for monitoring embedded devices
FH Bahnsen, J Kaiser, G Fey
2021 IEEE European Test Symposium (ETS), 1-4, 2021
32021
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
22023
Beam trajectory cocntrol with lattice-agnostic reinforcement learning
C Xu, E Bründermann, AS Müller, AS Garcia, J Kaiser, A Eichler
Proc. IPAC’23, 2023
22023
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
12024
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
12023
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
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
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
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Articles 1–12