| CHOMP: Gradient optimization techniques for efficient motion planning N Ratliff, M Zucker, JA Bagnell, S Srinivasa 2009 IEEE International Conference on Robotics and Automation, 489-494, 2009 | 612 | 2009 |
| Maximum margin planning ND Ratliff, JA Bagnell, MA Zinkevich Proceedings of the 23rd international conference on Machine learning, 729-736, 2006 | 582 | 2006 |
| Planning-based prediction for pedestrians BD Ziebart, N Ratliff, G Gallagher, C Mertz, K Peterson, JA Bagnell, ... 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2009 | 428 | 2009 |
| Chomp: Covariant hamiltonian optimization for motion planning M Zucker, N Ratliff, AD Dragan, M Pivtoraiko, M Klingensmith, CM Dellin, ... The International Journal of Robotics Research 32 (9-10), 1164-1193, 2013 | 391 | 2013 |
| Learning to search: structured prediction techniques for imitation learning ND Ratliff Carnegie Mellon University, 2009 | 236* | 2009 |
| Learning to search: Functional gradient techniques for imitation learning ND Ratliff, D Silver, JA Bagnell Autonomous Robots 27 (1), 25-53, 2009 | 213 | 2009 |
| Boosting structured prediction for imitation learning JA Bagnell, J Chestnutt, DM Bradley, ND Ratliff Advances in Neural Information Processing Systems, 1153-1160, 2007 | 156 | 2007 |
| Bispace planning: Concurrent multi-space exploration R Diankov, N Ratliff, D Ferguson, S Srinivasa, J Kuffner Proceedings of robotics: Science and systems IV 63, 2008 | 125 | 2008 |
| Closing the sim-to-real loop: Adapting simulation randomization with real world experience Y Chebotar, A Handa, V Makoviychuk, M Macklin, J Issac, N Ratliff, D Fox 2019 International Conference on Robotics and Automation (ICRA), 8973-8979, 2019 | 115 | 2019 |
| Imitation learning for locomotion and manipulation N Ratliff, JA Bagnell, SS Srinivasa 2007 7th IEEE-RAS International Conference on Humanoid Robots, 392-397, 2007 | 100 | 2007 |
| (Approximate) Subgradient Methods for Structured Prediction ND Ratliff, JA Bagnell, MA Zinkevich Artificial Intelligence and Statistics, 380-387, 2007 | 97 | 2007 |
| (Approximate) Subgradient Methods for Structured Prediction ND Ratliff, JA Bagnell, MA Zinkevich Artificial Intelligence and Statistics, 380-387, 2007 | 97 | 2007 |
| Optimization and learning for rough terrain legged locomotion M Zucker, N Ratliff, M Stolle, J Chestnutt, JA Bagnell, CG Atkeson, ... The International Journal of Robotics Research 30 (2), 175-191, 2011 | 91 | 2011 |
| Manipulation planning with goal sets using constrained trajectory optimization AD Dragan, ND Ratliff, SS Srinivasa 2011 IEEE International Conference on Robotics and Automation, 4582-4588, 2011 | 64 | 2011 |
| Subgradient methods for maximum margin structured learning N Ratliff, JA Bagnell, M Zinkevich ICML workshop on learning in structured output spaces 46, 2006 | 54 | 2006 |
| Inverse optimal heuristic control for imitation learning N Ratliff, B Ziebart, K Peterson, JA Bagnell, M Hebert, AK Dey, S Srinivasa Artificial Intelligence and Statistics, 424-431, 2009 | 49 | 2009 |
| The effects of repeated exposure on liking and judgments of musical unity of intact and patchwork compositions SL Tan, MP Spackman, CL Peaslee Music Perception 23 (5), 407-421, 2006 | 49 | 2006 |
| Direct Loss Minimization Inverse Optimal Control. A Doerr, ND Ratliff, J Bohg, M Toussaint, S Schaal Robotics: Science and Systems, 2015 | 37 | 2015 |
| Understanding the geometry of workspace obstacles in motion optimization N Ratliff, M Toussaint, S Schaal 2015 IEEE International Conference on Robotics and Automation (ICRA), 4202-4209, 2015 | 33 | 2015 |
| Semi-supervised learning with density based distances AS Bijral, N Ratliff, N Srebro arXiv preprint arXiv:1202.3702, 2012 | 31 | 2012 |
