| Information theoretic MPC for model-based reinforcement learning G Williams, N Wagener, B Goldfain, P Drews, JM Rehg, B Boots, ... IEEE International Conference on Robotics and Automation (ICRA), 1714-1721, 2017 | 464 | 2017 |
| Fast policy learning through imitation and reinforcement CA Cheng, X Yan, N Wagener, B Boots Uncertainty in Artificial Intelligence (UAI), 845-855, 2018 | 84 | 2018 |
| An online learning approach to model predictive control N Wagener*, CA Cheng*, J Sacks, B Boots Robotics: Science and Systems (RSS), 2019 | 68 | 2019 |
| Safe reinforcement learning using advantage-based intervention N Wagener, B Boots, CA Cheng International Conference on Machine Learning (ICML), 10630-10640, 2021 | 34 | 2021 |
| Learning contact-rich manipulation skills with guided policy search S Levine, N Wagener, P Abbeel IEEE International Conference on Robotics and Automation (ICRA), 156-163, 2015 | 18* | 2015 |
| Consistent dropout for policy gradient reinforcement learning M Hausknecht, N Wagener arXiv preprint arXiv:2202.11818, 2022 | 4 | 2022 |
| Exploiting singular configurations for controllable, low-power friction enhancement on unmanned ground vehicles A Foris, N Wagener, B Boots, A Mazumdar IEEE Robotics and Automation Letters (RA-L) 5 (2), 3556-3563, 2020 | 3 | 2020 |
| TerrainNet: Visual modeling of complex terrain for high-speed, off-road navigation X Meng, N Hatch, A Lambert, A Li, N Wagener, M Schmittle, JH Lee, ... Robotics: Science and Systems (RSS), 2023 | 2 | 2023 |
| MoCapAct: A multi-task dataset for simulated humanoid control N Wagener, A Kolobov, F Vieira Frujeri, R Loynd, CA Cheng, ... Advances in Neural Information Processing Systems (NeurIPS) 35, 35418-35431, 2022 | 2 | 2022 |
Byron BootsAssociate Professor, University of WashingtonVerified email at cs.washington.edu
