Byron Boots

Cited by

	All	Since 2016
Citations	3508	2840
h-index	32	29
i10-index	69	63

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Co-authors

Ching-An ChengSenior Researcher, Microsoft ResearchVerified email at microsoft.com
Xinyan YanGeorgia Institute of TechnologyVerified email at cc.gatech.edu
Mustafa MukadamResearch Scientist, Facebook AI ResearchVerified email at fb.com
Evangelos TheodorouGeorgia Institute of TechnologyVerified email at ae.gatech.edu
Dieter FoxProfessor of Computer Science and Engineering, University of Washington, and Nvidia ResearchVerified email at cs.washington.edu
Geoff GordonProfessor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Sajid SiddiqiGoogleVerified email at google.com
J. Andrew BagnellCarnegie Mellon UniversityVerified email at ri.cmu.edu
Yunpeng PanGeorgia Institute of TechnologyVerified email at gatech.edu
Wen SunAssistant Professor, Cornell UniversityVerified email at cs.cmu.edu
Frank DellaertProfessor, Georgia TechVerified email at cc.gatech.edu
Amirreza ShabanComputer Science PhD, University of WashingtonVerified email at uw.edu
Le SongGeorgia Institute of TechnologyVerified email at cc.gatech.edu
Nathan RatliffNVIDIAVerified email at nvidia.com
Jing DongFacebookVerified email at oculus.com
Arun VenkatramanAurora Innovation / past: Carnegie Mellon UniversityVerified email at cs.cmu.edu
Arunkumar ByravanResearch Scientist, DeepMindVerified email at google.com
Muhammad Asif RanaGeorgia Institute of TechnologyVerified email at gatech.edu
Kamil SaigolInstitute for Robotics and Intelligent Machines, Georgia Institute of TechnologyVerified email at gatech.edu
Sonia ChernovaAssociate Professor, Georgia Institute of TechnologyVerified email at cc.gatech.edu

Byron Boots

Associate Professor, University of Washington

Verified email at cs.washington.edu - Homepage

Machine Learning Artificial Intelligence Robotics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Closing the learning-planning loop with predictive state representations B Boots, SM Siddiqi, GJ Gordon The International Journal of Robotics Research 30 (7), 954-966, 2011	228	2011
Hilbert space embeddings of hidden Markov models L Song, B Boots, S Siddiqi, G Gordon, A Smola	222	2010
Information theoretic MPC for model-based reinforcement learning G Williams, N Wagener, B Goldfain, P Drews, JM Rehg, B Boots, ... 2017 IEEE International Conference on Robotics and Automation (ICRA), 1714-1721, 2017	186	2017
Deeply aggrevated: Differentiable imitation learning for sequential prediction W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell arXiv preprint arXiv:1703.01030, 2017	143	2017
Reduced-rank hidden Markov models S Siddiqi, B Boots, G Gordon Proceedings of the Thirteenth International Conference on Artificial …, 2010	136	2010
One-shot learning for semantic segmentation A Shaban, S Bansal, Z Liu, I Essa, B Boots arXiv preprint arXiv:1709.03410, 2017	130	2017
A constraint generation approach to learning stable linear dynamical systems S Siddiqi, B Boots, G Gordon CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF, 2008	130*	2008
Agile autonomous driving using end-to-end deep imitation learning Y Pan, CA Cheng, K Saigol, K Lee, X Yan, E Theodorou, B Boots arXiv preprint arXiv:1709.07174, 2017	127	2017
Differentiable mpc for end-to-end planning and control B Amos, I Jimenez, J Sacks, B Boots, JZ Kolter Advances in Neural Information Processing Systems, 8289-8300, 2018	89	2018
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs. J Dong, M Mukadam, F Dellaert, B Boots Robotics: Science and Systems 12, 4, 2016	79	2016
Hilbert space embeddings of predictive state representations B Boots, G Gordon, A Gretton arXiv preprint arXiv:1309.6819, 2013	79	2013
An online spectral learning algorithm for partially observable nonlinear dynamical systems B Boots, G Gordon Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 2011	74	2011
Learning from conditional distributions via dual embeddings B Dai, N He, Y Pan, B Boots, L Song Artificial Intelligence and Statistics, 1458-1467, 2017	71	2017
Percutaneous intracerebral navigation by duty-cycled spinning of flexible bevel-tipped needles JA Engh, DS Minhas, D Kondziolka, CN Riviere Neurosurgery 67 (4), 1117-1123, 2010	71	2010
Continuous-time Gaussian process motion planning via probabilistic inference M Mukadam, J Dong, X Yan, F Dellaert, B Boots The International Journal of Robotics Research 37 (11), 1319-1340, 2018	70	2018
Gaussian process motion planning M Mukadam, X Yan, B Boots 2016 IEEE international conference on robotics and automation (ICRA), 9-15, 2016	69	2016
4D crop monitoring: Spatio-temporal reconstruction for agriculture J Dong, JG Burnham, B Boots, G Rains, F Dellaert 2017 IEEE International Conference on Robotics and Automation (ICRA), 3878-3885, 2017	57	2017
Two-manifold problems with applications to nonlinear system identification B Boots, G Gordon arXiv preprint arXiv:1206.4648, 2012	54	2012
Functional gradient motion planning in reproducing kernel hilbert spaces Z Marinho, A Dragan, A Byravan, B Boots, S Srinivasa, G Gordon arXiv preprint arXiv:1601.03648, 2016	52	2016
Towards robust skill generalization: Unifying learning from demonstration and motion planning M Rana, M Mukadam, SR Ahmadzadeh, S Chernova, B Boots Intelligent robots and systems, 2018	49	2018

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