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Julian Ibarz

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Do As I Can, Not As I Say: Grounding Language in Robotic Affordances


Apr 04, 2022
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

* See website at https://say-can.github.io/ 

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MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance


Dec 07, 2021
Michael Luo, Ashwin Balakrishna, Brijen Thananjeyan, Suraj Nair, Julian Ibarz, Jie Tan, Chelsea Finn, Ion Stoica, Ken Goldberg

* Workshop on Safe and Robust Control of Uncertain Systems at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online 

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Visionary: Vision architecture discovery for robot learning


Mar 26, 2021
Iretiayo Akinola, Anelia Angelova, Yao Lu, Yevgen Chebotar, Dmitry Kalashnikov, Jacob Varley, Julian Ibarz, Michael S. Ryoo

* ICRA 2021 

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How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned


Feb 04, 2021
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine

* Journal of Robotics Research (IJRR), February 2021 

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Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones


Oct 29, 2020
Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg

* First two authors contributed equally 

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RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real


Jun 16, 2020
Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari

* Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020) 

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Thinking While Moving: Deep Reinforcement Learning with Concurrent Control


Apr 25, 2020
Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

* Published as a conference paper at ICLR 2020 

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