| Swad: Domain generalization by seeking flat minima J Cha, S Chun, K Lee, HC Cho, S Park, Y Lee, S Park Advances in Neural Information Processing Systems 34, 22405-22418, 2021 | 110 | 2021 |
| Uncertainty-aware learning from demonstration using mixture density networks with sampling-free variance modeling S Choi, K Lee, S Lim, S Oh 2018 IEEE International Conference on Robotics and Automation (ICRA), 6915-6922, 2018 | 85 | 2018 |
| Sparse markov decision processes with causal sparse tsallis entropy regularization for reinforcement learning K Lee, S Choi, S Oh IEEE Robotics and Automation Letters 3 (3), 1466-1473, 2018 | 48 | 2018 |
| Robust learning from demonstration using leveraged Gaussian processes and sparse-constrained optimization S Choi, K Lee, S Oh 2016 IEEE International Conference on Robotics and Automation (ICRA), 470-475, 2016 | 36 | 2016 |
| Monte carlo tree search in continuous spaces using voronoi optimistic optimization with regret bounds B Kim, K Lee, S Lim, L Kaelbling, T Lozano-Pérez Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 9916-9924, 2020 | 31 | 2020 |
| Robust learning from demonstrations with mixed qualities using leveraged gaussian processes S Choi, K Lee, S Oh IEEE Transactions on Robotics 35 (3), 564-576, 2019 | 26 | 2019 |
| Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots K Lee, S Kim, S Lim, S Choi, M Hong, J Kim, YL Park, S Oh Robotics: Science and Systems Foundation, 2020 | 22* | 2020 |
| Real-time nonparametric reactive navigation of mobile robots in dynamic environments S Choi, E Kim, K Lee, S Oh Robotics and Autonomous Systems 91, 11-24, 2017 | 22 | 2017 |
| Domain generalization by mutual-information regularization with pre-trained models J Cha, K Lee, S Park, S Chun Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 21 | 2022 |
| Distributional deep reinforcement learning with a mixture of Gaussians Y Choi, K Lee, S Oh 2019 International Conference on Robotics and Automation (ICRA), 9791-9797, 2019 | 18 | 2019 |
| Maximum causal tsallis entropy imitation learning K Lee, S Choi, S Oh Advances in Neural Information Processing Systems 31 (2018), 4403-4413., 2018 | 17 | 2018 |
| Inverse reinforcement learning with leveraged Gaussian processes K Lee, S Choi, S Oh 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 15 | 2016 |
| Mixgail: Autonomous driving using demonstrations with mixed qualities G Lee, D Kim, W Oh, K Lee, S Oh 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 13 | 2020 |
| Learning to walk a tripod mobile robot using nonlinear soft vibration actuators with entropy adaptive reinforcement learning JI Kim, M Hong, K Lee, DW Kim, YL Park, S Oh IEEE Robotics and Automation Letters 5 (2), 2317-2324, 2020 | 13 | 2020 |
| Leveraged non-stationary Gaussian process regression for autonomous robot navigation S Choi, E Kim, K Lee, S Oh 2015 IEEE International Conference on Robotics and Automation (ICRA), 473-478, 2015 | 13 | 2015 |
| Gaussian random paths for real-time motion planning S Choi, K Lee, S Oh 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 12 | 2016 |
| Optimal algorithms for stochastic multi-armed bandits with heavy tailed rewards K Lee, H Yang, S Lim, S Oh Advances in Neural Information Processing Systems 33, 8452-8462, 2020 | 11 | 2020 |
| Density matching reward learning S Choi, K Lee, A Park, S Oh arXiv preprint arXiv:1608.03694, 2016 | 8 | 2016 |
| Task agnostic robust learning on corrupt outputs by correlation-guided mixture density networks S Choi, S Hong, K Lee, S Lim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 7 | 2020 |
| Neural markov controlled SDE: Stochastic optimization for continuous-time data SW Park, K Lee, J Kwon International Conference on Learning Representations, 2022 | 6 | 2022 |
Songhwai OhDepartment of Electrical and Computer Engineering, Seoul National University, Koreasnu.ac.kr의 이메일 확인됨
