Follow
Byron Boots
Byron Boots
Associate Professor, University of Washington
Verified email at cs.washington.edu - Homepage
Title
Cited by
Cited by
Year
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
3342017
One-shot learning for semantic segmentation
A Shaban, S Bansal, Z Liu, I Essa, B Boots
arXiv preprint arXiv:1709.03410, 2017
2972017
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
2522011
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
2292017
Hilbert space embeddings of hidden Markov models
L Song, B Boots, S Siddiqi, G Gordon, A Smola
2252010
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 31, 2018
2042018
Deeply aggrevated: Differentiable imitation learning for sequential prediction
W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell
International conference on machine learning, 3309-3318, 2017
1902017
A constraint generation approach to learning stable linear dynamical systems
S Siddiqi, B Boots, G Gordon
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF, 2008
139*2008
Reduced-rank hidden Markov models
S Siddiqi, B Boots, G Gordon
Proceedings of the Thirteenth International Conference on Artificial …, 2010
1362010
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
1242018
Truncated back-propagation for bilevel optimization
A Shaban, CA Cheng, N Hatch, B Boots
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
1122019
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
1022016
Learning from conditional distributions via dual embeddings
B Dai, N He, Y Pan, B Boots, L Song
Artificial Intelligence and Statistics, 1458-1467, 2017
982017
Gaussian process motion planning
M Mukadam, X Yan, B Boots
2016 IEEE international conference on robotics and automation (ICRA), 9-15, 2016
932016
Hilbert space embeddings of predictive state representations
B Boots, G Gordon, A Gretton
arXiv preprint arXiv:1309.6819, 2013
902013
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
772017
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), 293-300, 2011
772011
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
712018
Variational inference for Gaussian process models with linear complexity
CA Cheng, B Boots
Advances in Neural Information Processing Systems 30, 2017
692017
Learning cognitive maps: Finding useful structure in an uncertain world
E Chown, B Boots
Robotics and Cognitive Approaches to Spatial Mapping, 215-236, 2007
66*2007
The system can't perform the operation now. Try again later.
Articles 1–20