| Safe Model-based Reinforcement Learning with Stability Guarantees F Berkenkamp, M Turchetta, AP Schoellig, A Krause Proc. of Neural Information Processing Systems (NeurIPS), 2017 | 839 | 2017 |
| Learning-based Model Predictive Control for Safe Exploration T Koller, F Berkenkamp, M Turchetta, A Krause Conference on Decision and Control (CDC), 2018 | 408 | 2018 |
| Safe controller optimization for quadrotors with Gaussian processes F Berkenkamp, AP Schoellig, A Krause Proc. of the International Conference on Robotics and Automation (ICRA), 491-496, 2016 | 296 | 2016 |
| Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning NY Siegel, JT Springenberg, F Berkenkamp, A Abdolmaleki, M Neunert, ... International Conference on Learning Representations (ICLR), 2020 | 241 | 2020 |
| Safe learning of regions of attraction for uncertain, nonlinear systems with gaussian processes F Berkenkamp, R Moriconi, AP Schoellig, A Krause 2016 IEEE 55th Conference on Decision and Control (CDC), 4661-4666, 2016 | 211 | 2016 |
| The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems SM Richards, F Berkenkamp, A Krause Conference on Robot Learning (CoRL), 2018 | 209 | 2018 |
| Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics F Berkenkamp, A Krause, AP Schoellig arXiv preprint arXiv:1602.04450, 2016 | 209* | 2016 |
| Safe exploration in finite Markov decision processes with Gaussian processes M Turchetta, F Berkenkamp, A Krause Advances in Neural Information Processing Systems (NeurIPS), 4312-4320, 2016 | 185 | 2016 |
| Safe and robust learning control with Gaussian processes F Berkenkamp, AP Schoellig Proc. of the European Control Conference (ECC), 2501-2506, 2015 | 183 | 2015 |
| Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization A Marco, F Berkenkamp, P Hennig, AP Schoellig, A Krause, S Schaal, ... Proc. of the International Conference on Robotics and Automation (ICRA …, 2017 | 137 | 2017 |
| Information-Directed Exploration for Deep Reinforcement Learning N Nikolov, J Kirschner, F Berkenkamp, A Krause International Conference on Learning Representations (ICLR), 2019 | 80 | 2019 |
| Safe Exploration for Interactive Machine Learning M Turchetta, F Berkenkamp, A Krause Advances in Neural Information Processing Systems (NeurIPS), 2887-2897, 2019 | 69 | 2019 |
| Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning S Curi*, F Berkenkamp*, A Krause Neural Information Processing Systems (NeurIPS), 2020 | 63 | 2020 |
| Bayesian optimization for maximum power point tracking in photovoltaic power plants H Abdelrahman, F Berkenkamp, J Poland, A Krause 2016 European Control Conference (ECC), 2078-2083, 2016 | 55 | 2016 |
| No-regret Bayesian Optimization with Unknown Hyperparameters F Berkenkamp, AP Schoellig, A Krause Journal of Machine Learning Research 20 (50), 1-24, 2019 | 54 | 2019 |
| Verifying Controllers Against Adversarial Examples with Bayesian Optimization S Ghosh, F Berkenkamp, G Ranade, S Qadeer, A Kapoor Proc. of the International Conference on Robotics and Automation (ICRA), 2018 | 53 | 2018 |
| Constrained Bayesian Optimization with Particle Swarms for Safe Adaptive Controller Tuning RRPR Duivenvoorden, F Berkenkamp, N Carion, A Krause, AP Schoellig IFAC World Congress, 2017 | 42 | 2017 |
| Hybrid model predictive control of stratified thermal storages in buildings F Berkenkamp, M Gwerder Energy and Buildings 84, 233-240, 2014 | 33 | 2014 |
| Safe exploration in reinforcement learning: Theory and applications in robotics F Berkenkamp ETH Zurich, 2019 | 30 | 2019 |
| Structured variational inference in partially observable unstable Gaussian process state space models S Curi, S Melchior, F Berkenkamp, A Krause Learning for Dynamics and Control, 147-157, 2020 | 14 | 2020 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
