Deep Model Predictive Control with Online Learning for Complex Physical Systems. - Katharina Bieker; Sebastian Peitz; Steven L. Brunton; J. Nathan Kutz; Michael Dellnitz (CoRR, 2019)

On the Treatment of Optimization Problems With L1 Penalty Terms via Multiobjective Continuation. - Katharina Bieker; Bennet Gebken; Sebastian Peitz (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

ParFam - Symbolic Regression Based on Continuous Global Optimization. - Philipp Scholl 003; Katharina Bieker; Hillary Hauger; Gitta Kutyniok (CoRR, 2023)

Optimization Techniques for Data-Based Control and Machine Learning. - Katharina Bieker (2023)

On the universal transformation of data-driven models to control systems. - Sebastian Peitz; Katharina Bieker (Autom., 2023)

On the structure of regularization paths for piecewise differentiable regularization terms. - Bennet Gebken; Katharina Bieker; Sebastian Peitz (J. Glob. Optim., 2023)

Compositional Construction of Barrier Functions for Switched Impulsive Systems. - Katharina Bieker; Hugo T. M. Kussaba; Philipp Scholl 003; Jaesug Jung; Abdalla Swikir; Sami Haddadin; Gitta Kutyniok (CDC, 2024)

ParFam - (Neural Guided) Symbolic Regression via Continuous Global Optimization. - Philipp Scholl 003; Katharina Bieker; Hillary Hauger; Gitta Kutyniok (ICLR, 2025)