Publications

  1. Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning: Jan Kaiser et al., arXiv, doi: 10.48550/arXiv.2306.03739
  2. Predictive Maintenance for the Optical Synchronization System of the European XFEL: A Systematic Literature Survey: Arne Grünhagen et al., BTW2023 - Datenbanksysteme für Business, Technologie und Web, doi: 10.18420/BTW2023-70
  3. Anomaly detection at the European X-ray Free Electron Laser using a parity-space-based method: Annika Eichler et al., Physical Review Accelerators and Beams, doi: 10.1103/PhysRevAccelBeams.26.012801
  4. Application of Machine Learning in Longitudinal Phase Space Prediction at the European XFEL: Zihan Zhu et al., Proceedings of the 40th International Free Electron Laser Conference (FEL2022), doi: https://indico.jacow.org/event/44/contributions/545/
  5. Convex Synthesis of Robust Distributed Controllers for the Optical Synchronization System at European XFEL: Maximilian Schütte et al., 2022 IEEE Conference on Control Technology and Applications (CCTA), doi: 10.1109/CCTA49430.2022.9966114
  6. Learning-based Optimisation of Particle Accelerators Under Partial Observability Without Real-World Training: Jan Kaiser et al., Proceedings of the 39th International Conference on Machine Learning, doi: https://proceedings.mlr.press/v162/kaiser22a.html
  7. Accelerating Linear Beam Dynamics Simulations for Machine Learning Applications: Oliver Stein et al., Proceedings of the 13th International Particle Accelerator Conference, doi: 10.18429/JACoW-IPAC2022-WEPOMS036
  8. Decentralized Output Feedback Control using Sparsity Invariance with Application to Synchronization at European XFEL: Maximilian Schütte et al., 2021 60th IEEE Conference on Decision and Control (CDC), doi: 10.1109/CDC45484.2021.9683027
  9. Fault Analysis of the Beam Acceleration Control System at the European XFEL using Data Mining: Arne Grünhagen et al., 2021 IEEE 30th Asian Test Symposium (ATS), doi: 10.1109/ATS52891.2021.00023
  10. First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT: Annika Eichler et al., Proceedings of the 12th International Particle Accelerator Conference, doi: 10.18429/JACoW-IPAC2021-TUPAB298
  11. Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE: Chenran Xu et al., Proceedings of the 12th International Particle Accelerator Conference, doi: 10.18429/JACoW-IPAC2021-WEPAB289
  12. High-Fidelity Prediction of Megapixel Longitudinal Phase-Space Images of Electron Beams Using Encoder-Decoder Neural Networks: J. Zhu et al., Phys. Rev. Applied, doi: https://doi.org/10.1103/PhysRevApplied.16.024005
  13. Model-based feed-forward control for time-varying systems with an example for SRF cavities: Sven Pfeiffer et al., IFAC-PapersOnLine, doi: 10.1016/j.ifacol.2020.12.1868
  14. Reduced model of plasma evolution in hydrogen discharge capillary plasmas: G. J. Boyle et al., Phys. Rev. E, doi: 10.1103/PhysRevE.104.015211
  15. Online Detuning Computation and Quench Detection for Superconducting Resonators: Andrea Bellandi et al., IEEE Trans. Nucl. Sci., doi: 10.1109/TNS.2021.3067598
  16. Automation and control of laser wakefield accelerators using Bayesian optimization: R. J. Shalloo et al., Nat Commun, doi: 10.1038/s41467-020-20245-6
  17. Physics-based deep neural networks for beam dynamics in charged particle accelerators: Andrei Ivanov et al., Phys. Rev. Accel. Beams, doi: 10.1103/PhysRevAccelBeams.23.074601
  18. Distributed Model Predictive Control for Linear Systems With Adaptive Terminal Sets: Georgios Darivianakis et al., IEEE Trans. Automat. Contr., doi: 10.1109/TAC.2019.2916774
  19. FPGA-Based RF and Piezocontrollers for SRF Cavities in CW Mode: Radoslaw Rybaniec et al., IEEE Trans. Nucl. Sci., doi: 10.1109/TNS.2017.2687981