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Picture for Thomas Rothörl

S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency


Oct 13, 2020
Mel Vecerik, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Christopher Schuster, Raia Hadsell, Lourdes Agapito, Jonathan Scholz

* 11 pages, supplementary material available at: https://sites.google.com/view/2020-s3k/home 

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Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards


Oct 08, 2018
Mel Vecerik, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin Riedmiller


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A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning


Oct 08, 2018
Mel Vecerik, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jon Scholz


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Sim-to-Real Robot Learning from Pixels with Progressive Nets


May 22, 2018
Andrei A. Rusu, Mel Vecerik, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell


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Learning Awareness Models


Apr 17, 2018
Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gómez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil

* Accepted to ICLR 2018 

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