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Thomas Rothörl
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2020 – today
- 2020
- [c4]Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Raia Hadsell, Lourdes Agapito, Jonathan Scholz:
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRL 2020: 449-460 - [i6]Mel Vecerík, Jean-Baptiste Regli, Oleg Sushkov, David Barker, Rugile Pevceviciute, Thomas Rothörl, Christopher Schuster, Raia Hadsell, Lourdes Agapito, Jonathan Scholz:
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency. CoRR abs/2009.14711 (2020)
2010 – 2019
- 2019
- [c3]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. ICRA 2019: 754-760 - [i5]Rae Jeong, Jackie Kay, Francesco Romano, Thomas Lampe, Thomas Rothörl, Abbas Abdolmaleki, Tom Erez, Yuval Tassa, Francesco Nori:
Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer. CoRR abs/1910.09471 (2019) - 2018
- [c2]Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil:
Learning Awareness Models. ICLR (Poster) 2018 - [i4]Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil:
Learning Awareness Models. CoRR abs/1804.06318 (2018) - [i3]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. CoRR abs/1810.01531 (2018) - 2017
- [c1]Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell:
Sim-to-Real Robot Learning from Pixels with Progressive Nets. CoRL 2017: 262-270 - [i2]Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller:
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR abs/1707.08817 (2017) - 2016
- [i1]Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell:
Sim-to-Real Robot Learning from Pixels with Progressive Nets. CoRR abs/1610.04286 (2016)
Coauthor Index

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