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AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale


Nov 11, 2021
Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine


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AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale


Nov 09, 2021
Yao Lu, Karol Hausman, Yevgen Chebotar, Mengyuan Yan, Eric Jang, Alexander Herzog, Ted Xiao, Alex Irpan, Mohi Khansari, Dmitry Kalashnikov, Sergey Levine


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Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills


Apr 28, 2021
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jake Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine


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Meta-Learning Requires Meta-Augmentation


Jul 10, 2020
Janarthanan Rajendran, Alex Irpan, Eric Jang

* 14 pages, 8 figures. Code at https://github.com/google-research/google-research/tree/master/maml_nonexclusive 

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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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Off-Policy Evaluation via Off-Policy Classification


Jun 20, 2019
Alex Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine

* Accepted to ICML 2019 RL4RealLife workshop 

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The Principle of Unchanged Optimality in Reinforcement Learning Generalization


Jun 02, 2019
Alex Irpan, Xingyou Song

* Published at ICML 2019 Workshop "Understanding and Improving Generalization in Deep Learning" 

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Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks


Mar 25, 2019
Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, Konstantinos Bousmalis

* To be published in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019) 

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QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation


Nov 28, 2018
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine

* CoRL 2018 camera ready. 23 pages, 14 figures 

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Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors


Oct 31, 2018
Danijar Hafner, Dustin Tran, Timothy Lillicrap, Alex Irpan, James Davidson

* 9 pages, 5 figures 

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Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?


Jun 29, 2018
Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon Kleinberg

* Accepted to ICML 2018, code opensourced at: https://github.com/rubai5/ESS_Game 

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Learning Hierarchical Information Flow with Recurrent Neural Modules


Nov 04, 2017
Danijar Hafner, Alex Irpan, James Davidson, Nicolas Heess

* NIPS 2017 

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Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping


Sep 25, 2017
Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, Vincent Vanhoucke

* 9 pages, 5 figures, 3 tables 

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