Bayesian Optimization for Policy Search in High-Dimensional Systems via Automatic Domain Selection. - Lukas P. Fröhlich; Edgar D. Klenske; Christian G. Daniel; Melanie N. Zeilinger (IROS, 2019)

Meta-Learning Acquisition Functions for Bayesian Optimization. - Michael Volpp; Lukas P. Fröhlich; Andreas Doerr; Frank Hutter; Christian Daniel (CoRR, 2019)

Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization. - Lukas P. Fröhlich; Edgar D. Klenske; Julia Vinogradska; Christian Daniel; Melanie N. Zeilinger (AISTATS, 2020)

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. - Michael Volpp; Lukas P. Fröhlich; Kirsten Fischer; Andreas Doerr; Stefan Falkner; Frank Hutter; Christian Daniel (ICLR, 2020)

On Simulation and Trajectory Prediction with Gaussian Process Dynamics. - Lukas Hewing; Elena Arcari; Lukas P. Fröhlich; Melanie N. Zeilinger (L4DC, 2020)

Cautious Bayesian Optimization for Efficient and Scalable Policy Search. - Lukas P. Fröhlich; Melanie N. Zeilinger; Edgar D. Klenske (L4DC, 2021)

Model Learning and Contextual Controller Tuning for Autonomous Racing. - Lukas P. Fröhlich; Christian Küttel; Elena Arcari; Lukas Hewing; Melanie N. Zeilinger; Andrea Carron (CoRR, 2021)

On-Policy Model Errors in Reinforcement Learning. - Lukas P. Fröhlich; Maksym Lefarov; Melanie N. Zeilinger; Felix Berkenkamp (ICLR, 2022)

Contextual Tuning of Model Predictive Control for Autonomous Racing. - Lukas P. Fröhlich; Christian Küttel; Elena Arcari; Lukas Hewing; Melanie N. Zeilinger; Andrea Carron (IROS, 2022)

Data-Efficient Controller Tuning and Reinforcement Learning. - Lukas P. Fröhlich (2022)