| Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models K Chua, R Calandra, R McAllister, S Levine Advances in Neural Information Processing Systems 31, 2018 | 1459 | 2018 |
| Learning invariant representations for reinforcement learning without reconstruction A Zhang, R McAllister, R Calandra, Y Gal, S Levine arXiv preprint arXiv:2006.10742, 2020 | 481 | 2020 |
| DIGIT: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation M Lambeta, PW Chou, S Tian, B Yang, B Maloon, VR Most, D Stroud, ... IEEE Robotics and Automation Letters 5 (3), 3838-3845, 2020 | 437 | 2020 |
| Bayesian optimization for learning gaits under uncertainty: An experimental comparison on a dynamic bipedal walker R Calandra, A Seyfarth, J Peters, MP Deisenroth Annals of Mathematics and Artificial Intelligence 76, 5-23, 2016 | 383 | 2016 |
| More than a feeling: Learning to grasp and regrasp using vision and touch R Calandra, A Owens, D Jayaraman, J Lin, W Yuan, J Malik, EH Adelson, ... IEEE Robotics and Automation Letters 3 (4), 3300-3307, 2018 | 375 | 2018 |
| Manifold Gaussian processes for regression R Calandra, J Peters, CE Rasmussen, MP Deisenroth 2016 International Joint Conference on Neural Networks (IJCNN), 3338-3345, 2016 | 359 | 2016 |
| Adversarial continual learning S Ebrahimi, F Meier, R Calandra, T Darrell, M Rohrbach European Conference on Computer Vision, 386-402, 2020 | 228 | 2020 |
| The feeling of success: Does touch sensing help predict grasp outcomes? R Calandra, A Owens, M Upadhyaya, W Yuan, J Lin, EH Adelson, ... Conference on Robot Learning (CORL), 314-323, 2017 | 210 | 2017 |
| Low-level control of a quadrotor with deep model-based reinforcement learning NO Lambert, DS Drew, J Yaconelli, S Levine, R Calandra, KSJ Pister IEEE Robotics and Automation Letters 4 (4), 4224-4230, 2019 | 181 | 2019 |
| Manipulation by feel: Touch-based control with deep predictive models S Tian, F Ebert, D Jayaraman, M Mudigonda, C Finn, R Calandra, ... 2019 International Conference on Robotics and Automation (ICRA), 818-824, 2019 | 143 | 2019 |
| Goal-driven dynamics learning via Bayesian optimization S Bansal, R Calandra, T Xiao, S Levine, CJ Tomlin 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5168-5173, 2017 | 141 | 2017 |
| TACTO: A Fast, Flexible, and Open-Source Simulator for High-Resolution Vision-Based Tactile Sensors S Wang, M Lambeta, PW Chou, R Calandra IEEE Robotics and Automation Letters 7 (2), 3930-3937, 2022 | 126 | 2022 |
| On the importance of hyperparameter optimization for model-based reinforcement learning B Zhang, R Rajan, L Pineda, N Lambert, A Biedenkapp, K Chua, F Hutter, ... International Conference on Artificial Intelligence and Statistics, 4015-4023, 2021 | 121 | 2021 |
| OmniTact: A Multi-Directional High-Resolution Touch Sensor A Padmanabha, F Ebert, S Tian, R Calandra, C Finn, S Levine 2020 IEEE International Conference on Robotics and Automation (ICRA), 618-624, 2020 | 117 | 2020 |
| Re-examining linear embeddings for high-dimensional Bayesian optimization B Letham, R Calandra, A Rai, E Bakshy Advances in Neural Information Processing Systems 33, 2020 | 117 | 2020 |
| An experimental comparison of Bayesian optimization for bipedal locomotion R Calandra, A Seyfarth, J Peters, MP Deisenroth 2014 IEEE International Conference on Robotics and Automation (ICRA), 1951-1958, 2014 | 111 | 2014 |
| Active tactile object exploration with gaussian processes Z Yi, R Calandra, F Veiga, H van Hoof, T Hermans, Y Zhang, J Peters 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 106 | 2016 |
| Model-based meta-reinforcement learning for flight with suspended payloads S Belkhale, R Li, G Kahn, R McAllister, R Calandra, S Levine IEEE Robotics and Automation Letters 6 (2), 1471-1478, 2021 | 105 | 2021 |
| Bayesian gait optimization for bipedal locomotion R Calandra, N Gopalan, A Seyfarth, J Peters, MP Deisenroth International conference on learning and intelligent optimization, 274-290, 2014 | 102 | 2014 |
| Objective mismatch in model-based reinforcement learning N Lambert, B Amos, O Yadan, R Calandra Learning for Dynamics and Control (L4DC), 761-770, 2020 | 95 | 2020 |
Sergey LevineUC Berkeley, Physical IntelligenceZweryfikowany adres z eecs.berkeley.edu
