Andreas Doerr

According to our database, Andreas Doerr authored at least 9 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Models for data-efficient reinforcement learning on real-world applications.

Andreas Doerr

PhD thesis, 2021

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Meta-Learning Acquisition Functions for Bayesian Optimization.

Michael Volpp, Lukas P. Fröhlich, Andreas Doerr, Frank Hutter, Christian Daniel

CoRR, 2019

Trajectory-Based Off-Policy Deep Reinforcement Learning.

Andreas Doerr, Michael Volpp, Marc Toussaint, Sebastian Trimpe, Christian Daniel

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds.

David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Probabilistic Recurrent State-Space Models.

Andreas Doerr, Christian Daniel, Martin Schiegg, Duy Nguyen-Tuong, Stefan Schaal, Marc Toussaint, Sebastian Trimpe

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Model-based policy search for automatic tuning of multivariate PID controllers.

Andreas Doerr, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Sebastian Trimpe

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Optimizing Long-term Predictions for Model-based Policy Search.

Andreas Doerr, Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2015

Direct Loss Minimization Inverse Optimal Control.

Andreas Doerr, Nathan D. Ratliff, Jeannette Bohg, Marc Toussaint, Stefan Schaal

Proceedings of the Robotics: Science and Systems XI, Sapienza University of Rome, 2015