Peitz, S., &; Bieker, K. (2023). On the Universal Transformation of Data-Driven Models to Control Systems. Automatica, 149, Article 110840.https://doi.org/10.1016/j.automatica.2022.110840 
LibreCat: /record/21199
DOI: 10.1016/j.automatica.2022.110840

Gebken, B., Bieker, K., &; Peitz, S. (2023). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization, 85(3), 709–741.https://doi.org/10.1007/s10898-022-01223-2 
LibreCat: /record/27426
DOI: 10.1007/s10898-022-01223-2

Bieker, K., Gebken, B., &; Peitz, S. (2022). On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7797–7808.https://doi.org/10.1109/TPAMI.2021.3114962 
LibreCat: /record/20731
DOI: 10.1109/TPAMI.2021.3114962

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