Julian Ibarz
Cited by
Cited by
In-datacenter performance analysis of a tensor processing unit
NP Jouppi, C Young, N Patil, D Patterson, G Agrawal, R Bajwa, S Bates, ...
Proceedings of the 44th Annual International Symposium on Computer …, 2017
Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
S Levine, P Pastor, A Krizhevsky, J Ibarz, D Quillen
The International Journal of Robotics Research 37 (4-5), 421-436, 2018
Multi-digit number recognition from street view imagery using deep convolutional neural networks
IJ Goodfellow, Y Bulatov, J Ibarz, S Arnoud, V Shet
arXiv preprint arXiv:1312.6082, 2013
Using simulation and domain adaptation to improve efficiency of deep robotic grasping
K Bousmalis, A Irpan, P Wohlhart, Y Bai, M Kelcey, M Kalakrishnan, ...
2018 IEEE international conference on robotics and automation (ICRA), 4243-4250, 2018
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
Diversity is all you need: Learning skills without a reward function
B Eysenbach, A Gupta, J Ibarz, S Levine
arXiv preprint arXiv:1802.06070, 2018
Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks
S James, P Wohlhart, M Kalakrishnan, D Kalashnikov, A Irpan, J Ibarz, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
Attention-based extraction of structured information from street view imagery
Z Wojna, AN Gorban, DS Lee, K Murphy, Q Yu, Y Li, J Ibarz
2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017
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
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
Discrete sequential prediction of continuous actions for deep rl
L Metz, J Ibarz, N Jaitly, J Davidson
arXiv preprint arXiv:1705.05035, 2017
Leave no trace: Learning to reset for safe and autonomous reinforcement learning
B Eysenbach, S Gu, J Ibarz, S Levine
arXiv preprint arXiv:1711.06782, 2017
End-to-end learning of semantic grasping
E Jang, S Vijayanarasimhan, P Pastor, J Ibarz, S Levine
arXiv preprint arXiv:1707.01932, 2017
End-to-end interpretation of the french street name signs dataset
R Smith, C Gu, DS Lee, H Hu, R Unnikrishnan, J Ibarz, S Arnoud, S Lin
European Conference on Computer Vision, 411-426, 2016
Sequence transcription with deep neural networks
J Ibarz, Y Bulatov, I Goodfellow
US Patent 8,965,112, 2015
Updating geographic data based on a transaction
M Zennaro, K man Cheung, J Ibarz, L Yatziv, SC Arnoud
US Patent 8,868,522, 2014
Three-dimensional esophageal reconstruction
J Ibarz, N Strobel, L Yatziv
US Patent 8,538,106, 2013
System and method for view-dependent anatomic surface visualization
J Ibarz, L Yatziv, N Strobel
US Patent App. 12/875,191, 2011
Off-policy evaluation via off-policy classification
A Irpan, K Rao, K Bousmalis, C Harris, J Ibarz, S Levine
Advances in Neural Information Processing Systems, 5437-5448, 2019
Large scale business discovery from street level imagery
Q Yu, C Szegedy, MC Stumpe, L Yatziv, V Shet, J Ibarz, S Arnoud
arXiv preprint arXiv:1512.05430, 2015
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