Andreas Doerr

Publication Activity (10 Years)

Years Active: 2015-2020
Publications (10 Years): 10

Top Topics

Loss Minimization

Reinforcement Learning

Gaussian Process

Top Venues

Publications

Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. ICLR (2020)
Andreas Doerr, Michael Volpp, Marc Toussaint, Sebastian Trimpe, Christian Daniel
Trajectory-Based Off-Policy Deep Reinforcement Learning. ICML (2019)
Andreas Doerr, Michael Volpp, Marc Toussaint, Sebastian Trimpe, Christian Daniel
Trajectory-Based Off-Policy Deep Reinforcement Learning. CoRR (2019)
Michael Volpp, Lukas P. Fröhlich, Andreas Doerr, Frank Hutter, Christian Daniel
Meta-Learning Acquisition Functions for Bayesian Optimization. CoRR (2019)
Andreas Doerr, Christian Daniel, Martin Schiegg, Duy Nguyen-Tuong, Stefan Schaal, Marc Toussaint, Sebastian Trimpe
Probabilistic Recurrent State-Space Models. ICML (2018)
David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. CoRR (2018)
David Reeb, Andreas Doerr, Sebastian Gerwinn, Barbara Rakitsch
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. NeurIPS (2018)
Andreas Doerr, Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe
Optimizing Long-term Predictions for Model-based Policy Search. CoRL (2017)
Andreas Doerr, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Sebastian Trimpe
Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers. CoRR (2017)
Andreas Doerr, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Sebastian Trimpe
Model-based policy search for automatic tuning of multivariate PID controllers. ICRA (2017)
Andreas Doerr, Nathan D. Ratliff, Jeannette Bohg, Marc Toussaint, Stefan Schaal
Direct Loss Minimization Inverse Optimal Control. Robotics: Science and Systems (2015)