Eric Jang
Eric Jang
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Title
Cited by
Cited by
Year
Categorical reparameterization with gumbel-softmax
E Jang, S Gu, B Poole
arXiv preprint arXiv:1611.01144, 2016
15482016
Time-Contrastive Networks: Self-Supervised Learning from Pixels
P Sermanet, C Lynch, Y Chebotar, J Hsu, E Jang, S Schaal, S Levine
2018 IEEE International Conference on Robotics and Automation (ICRA), 2017
266*2017
Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation
D Kalashnikov, A Irpan, P Pastor, J Ibarz, A Herzog, E Jang, D Quillen, ...
arXiv preprint arXiv:1806.10293, 2018
2492018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
H Choi, E Jang, AA Alemi
arXiv preprint arXiv:1810.01392, 2018
98*2018
Deep reinforcement learning for vision-based robotic grasping: A simulated comparative evaluation of off-policy methods
D Quillen, E Jang, O Nachum, C Finn, J Ibarz, S Levine
2018 IEEE International Conference on Robotics and Automation (ICRA), 6284-6291, 2018
882018
Scalable deep reinforcement learning for vision-based robotic manipulation
D Kalashnikov, A Irpan, P Pastor, J Ibarz, A Herzog, E Jang, D Quillen, ...
Conference on Robot Learning, 651-673, 2018
872018
Sim2real viewpoint invariant visual servoing by recurrent control
F Sadeghi, A Toshev, E Jang, S Levine
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
80*2018
Grasp2vec: Learning object representations from self-supervised grasping
E Jang, C Devin, V Vanhoucke, S Levine
Proceedings of Machine Learning Research 87, 99-112, 2018
592018
End-to-end learning of semantic grasping
E Jang, S Vijayanarasimhan, P Pastor, J Ibarz, S Levine
Proceedings of Machine Learning Research 78, 119-132, 2017
462017
Categorical reparametrization with gumble-softmax
E Jang, S Gu, B Poole
International Conference on Learning Representations (ICLR 2017), 2017
452017
Watch, try, learn: Meta-learning from demonstrations and reward
A Zhou, E Jang, D Kappler, A Herzog, M Khansari, P Wohlhart, Y Bai, ...
arXiv preprint arXiv:1906.03352, 2019
82019
Deep machine learning methods and apparatus for robotic grasping
S Vijayanarasimhan, E Jang, PP Sampedro, S Levine
US Patent 9,914,213, 2018
62018
Emergence of selectivity to looming stimuli in a spiking network model of the optic tectum
EV Jang, C Ramirez-Vizcarrondo, CD Aizenman, AS Khakhalin
Frontiers in neural circuits 10, 95, 2016
52016
Scalable multi-task imitation learning with autonomous improvement
A Singh, E Jang, A Irpan, D Kappler, M Dalal, S Levine, M Khansari, ...
arXiv preprint arXiv:2003.02636, 2020
22020
RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer
D Ho, K Rao, Z Xu, E Jang, M Khansari, Y Bai
arXiv preprint arXiv:2011.03148, 2020
12020
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control
T Xiao, E Jang, D Kalashnikov, S Levine, J Ibarz, K Hausman, A Herzog
arXiv preprint arXiv:2004.06089, 2020
12020
Meta-learning requires meta-augmentation
J Rajendran, A Irpan, E Jang
Advances in Neural Information Processing Systems 33, 2020
12020
Machine learning methods and apparatus for semantic robotic grasping
E Jang, S Vijayanarasimhan, PP Sampedro, J Ibarz, S Levine
US Patent App. 16/622,309, 2020
2020
Deep machine learning methods and apparatus for robotic grasping
S Vijayanarasimhan, E Jang, PP Sampedro, S Levine
US Patent App. 16/823,947, 2020
2020
Self-supervised robotic object interaction
EV Jang, SV Levine, CM Devin
US Patent App. 16/443,765, 2019
2019
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