S. Peitz and K. Bieker, “On the Universal Transformation of Data-Driven Models to Control Systems,”10.1016/j.automatica.2022.110840__Automatica, vol. 149, Art. no. 110840, 2023, doi:10.1016/j.automatica.2022.110840 .
LibreCat: /record/21199
DOI: 10.1016/j.automatica.2022.110840

B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,”10.1007/s10898-022-01223-2__Journal of Global Optimization, vol. 85, no. 3, pp. 709–741, 2023, doi:10.1007/s10898-022-01223-2 .
LibreCat: /record/27426
DOI: 10.1007/s10898-022-01223-2

K. Bieker, B. Gebken, and S. Peitz, “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation,”10.1109/TPAMI.2021.3114962__IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 11, pp. 7797–7808, 2022, doi:10.1109/TPAMI.2021.3114962 .
LibreCat: /record/20731
DOI: 10.1109/TPAMI.2021.3114962

K. Bieker, S. Peitz, S. L. Brunton, J. N. Kutz, and M. Dellnitz, “Deep model predictive flow control with limited sensor data and online learning,” Theoretical and Computational Fluid Dynamics, vol. 34, pp. 577–591, 2020.
LibreCat: /record/16290
DOI: 10.1007/s00162-020-00520-4