| Safe model-based reinforcement learning with stability guarantees F Berkenkamp, M Turchetta, A Schoellig, A Krause Advances in neural information processing systems 30, 2017 | 735 | 2017 |
| Learning-based model predictive control for safe exploration T Koller, F Berkenkamp, M Turchetta, A Krause 2018 IEEE conference on decision and control (CDC), 6059-6066, 2018 | 352 | 2018 |
| Safe exploration in finite markov decision processes with gaussian processes M Turchetta, F Berkenkamp, A Krause Advances in Neural Information Processing Systems 29, 2016 | 170 | 2016 |
| Reinforced imitation: Sample efficient deep reinforcement learning for mapless navigation by leveraging prior demonstrations M Pfeiffer, S Shukla, M Turchetta, C Cadena, A Krause, R Siegwart, ... IEEE Robotics and Automation Letters 3 (4), 4423-4430, 2018 | 143 | 2018 |
| Safe exploration for interactive machine learning M Turchetta, F Berkenkamp, A Krause Advances in Neural Information Processing Systems 32, 2019 | 62 | 2019 |
| Safe reinforcement learning via curriculum induction M Turchetta, A Kolobov, S Shah, A Krause, A Agarwal Advances in Neural Information Processing Systems 33, 12151-12162, 2020 | 57 | 2020 |
| Mixed-variable Bayesian optimization E Daxberger, A Makarova, M Turchetta, A Krause arXiv preprint arXiv:1907.01329, 2019 | 31 | 2019 |
| Robust model-free reinforcement learning with multi-objective Bayesian optimization M Turchetta, A Krause, S Trimpe 2020 IEEE International Conference on Robotics and Automation (ICRA), 10702 …, 2020 | 23 | 2020 |
| Safe and efficient model-free adaptive control via bayesian optimization C König, M Turchetta, J Lygeros, A Rupenyan, A Krause 2021 IEEE International Conference on Robotics and Automation (ICRA), 9782-9788, 2021 | 14 | 2021 |
| Gosafe: Globally optimal safe robot learning D Baumann, A Marco, M Turchetta, S Trimpe 2021 IEEE International Conference on Robotics and Automation (ICRA), 4452-4458, 2021 | 8 | 2021 |
| Scalable safe exploration for global optimization of dynamical systems B Sukhija, M Turchetta, D Lindner, A Krause, S Trimpe, D Baumann arXiv preprint arXiv:2201.09562, 2022 | 4 | 2022 |
| Information directed reward learning for reinforcement learning D Lindner, M Turchetta, S Tschiatschek, K Ciosek, A Krause Advances in Neural Information Processing Systems 34, 3850-3862, 2021 | 4 | 2021 |
| Calibration of agent based transport simulations with multi-fidelity Bayesian optimization M Turchetta, A Makarova, S Beyeler, A Krause 18th Swiss Transport Research Conference (STRC 2018), 2018 | 2 | 2018 |
| Near-Optimal Multi-Agent Learning for Safe Coverage Control M Prajapat, M Turchetta, M Zeilinger, A Krause Advances in Neural Information Processing Systems 35, 14998-15012, 2022 | 1 | 2022 |
| Learning long-term crop management strategies with CyclesGym M Turchetta, L Corinzia, S Sussex, A Burton, J Herrera, I Athanasiadis, ... Advances in Neural Information Processing Systems 35, 11396-11409, 2022 | 1 | 2022 |
| Safety and Robustness in Reinforcement Learning M Turchetta ETH Zurich, 2021 | 1 | 2021 |
| Mixed-Variable Bayesian Optimization AK Krause, EAD Daxberger, EA Daxberger, MT Turchetta, M Turchetta, ... | | 2019 |
| Learning-based Model Predictive Control for Safe Reinforcement Learning T Koller, F Berkenkamp, M Turchetta, J Bödecker, A Krause Robust autonomy: tools for safety in real-world uncertain environments, 0 | | |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
