Artigos com autorizações de acesso público - J. Andrew BagnellSaiba mais
1 artigo não disponível publicamente
Autonomy infused teleoperation with application to brain computer interface controlled manipulation
K Muelling, A Venkatraman, JS Valois, JE Downey, J Weiss, S Javdani, ...
Autonomous Robots 41, 1401-1422, 2017
Autorizações: US National Science Foundation, US Department of Defense, US Department of …
28 artigos disponíveis publicamente
An algorithmic perspective on imitation learning
T Osa, J Pajarinen, G Neumann, JA Bagnell, P Abbeel, J Peters
Foundations and Trends® in Robotics 7 (1-2), 1-179, 2018
Autorizações: US National Science Foundation, US Department of Defense, European Commission
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
Autorizações: US Department of Defense
Shared autonomy via hindsight optimization for teleoperation and teaming
S Javdani, H Admoni, S Pellegrinelli, SS Srinivasa, JA Bagnell
The International Journal of Robotics Research 37 (7), 717-742, 2018
Autorizações: US National Science Foundation, US Department of Defense, European Commission
A discriminative framework for anomaly detection in large videos
A Del Giorno, JA Bagnell, M Hebert
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
Autorizações: US National Science Foundation
Shared autonomy via hindsight optimization
S Javdani, SS Srinivasa, JA Bagnell
Robotics science and systems: online proceedings 2015, 2015
Autorizações: US National Institutes of Health
Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping
JE Downey, JM Weiss, K Muelling, A Venkatraman, JS Valois, M Hebert, ...
Journal of neuroengineering and rehabilitation 13, 1-12, 2016
Autorizações: US National Science Foundation, US National Institutes of Health, US …
Provably efficient imitation learning from observation alone
W Sun, A Vemula, B Boots, D Bagnell
International conference on machine learning, 6036-6045, 2019
Autorizações: US Department of Defense
Learning anytime predictions in neural networks via adaptive loss balancing
H Hu, D Dey, M Hebert, JA Bagnell
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3812-3821, 2019
Autorizações: US Department of Defense
Dual policy iteration
W Sun, GJ Gordon, B Boots, J Bagnell
Advances in Neural Information Processing Systems 31, 2018
Autorizações: US Department of Defense
Of moments and matching: A game-theoretic framework for closing the imitation gap
G Swamy, S Choudhury, JA Bagnell, S Wu
International Conference on Machine Learning, 10022-10032, 2021
Autorizações: US National Science Foundation
Near optimal bayesian active learning for decision making
S Javdani, Y Chen, A Karbasi, A Krause, D Bagnell, S Srinivasa
Artificial Intelligence and Statistics, 430-438, 2014
Autorizações: European Commission
Submodular surrogates for value of information
Y Chen, S Javdani, A Karbasi, J Bagnell, S Srinivasa, A Krause
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Autorizações: European Commission
Learning to filter with predictive state inference machines
W Sun, A Venkatraman, B Boots, JA Bagnell
International conference on machine learning, 1197-1205, 2016
Autorizações: US National Science Foundation
A convex polynomial model for planar sliding mechanics: theory, application, and experimental validation
J Zhou, MT Mason, R Paolini, D Bagnell
The International Journal of Robotics Research 37 (2-3), 249-265, 2018
Autorizações: US National Science Foundation, US Department of Defense
Improved learning of dynamics models for control
A Venkatraman, R Capobianco, L Pinto, M Hebert, D Nardi, JA Bagnell
2016 International Symposium on Experimental Robotics, 703-713, 2017
Autorizações: US National Science Foundation, US Department of Defense
Predictive-state decoders: Encoding the future into recurrent networks
A Venkatraman, N Rhinehart, W Sun, L Pinto, M Hebert, B Boots, K Kitani, ...
Advances in Neural Information Processing Systems 30, 2017
Autorizações: US National Science Foundation, US Department of Defense
A probabilistic planning framework for planar grasping under uncertainty
J Zhou, R Paolini, AM Johnson, JA Bagnell, MT Mason
IEEE Robotics and Automation Letters 2 (4), 2111-2118, 2017
Autorizações: US National Science Foundation
Spatio-temporal matching for human pose estimation in video
F Zhou, F De la Torre
IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (8), 1492-1504, 2016
Autorizações: US National Science Foundation
Sequence model imitation learning with unobserved contexts
G Swamy, S Choudhury, J Bagnell, SZ Wu
Advances in Neural Information Processing Systems 35, 17665-17676, 2022
Autorizações: US National Science Foundation
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