Coline Devin

According to our database, Coline Devin authored at least 26 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.

CoRR, 2023

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, Jose Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

CoRR, 2023

2022

How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation.

Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors.

Charles Sun, Jedrzej Orbik, Coline Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

CoRR, 2021

Modular Networks for Compositional Instruction Following.

Rodolfo Corona, Daniel Fried, Coline Devin, Dan Klein, Trevor Darrell

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Learning to Reach Goals via Iterated Supervised Learning.

Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.

Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation.

Charles Sun, Jedrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes.

Alex X. Lee, Coline Manon Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Compositionality and Modularity for Robot Learning.

Coline Devin

PhD thesis, 2020

Modularity Improves Out-of-Domain Instruction Following.

Rodolfo Corona, Daniel Fried, Coline Devin, Dan Klein, Trevor Darrell

CoRR, 2020

Self-Supervised Goal-Conditioned Pick and Place.

Coline Devin, Payam Rowghanian, Chris Vigorito, William Richards, Khashayar Rohanimanesh

CoRR, 2020

2019

Learning To Reach Goals Without Reinforcement Learning.

Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine

CoRR, 2019

SMiRL: Surprise Minimizing RL in Dynamic Environments.

Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2019

Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control.

Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine

CoRR, 2019

Compositional Plan Vectors.

Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Monocular Plan View Networks for Autonomous Driving.

Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krähenbühl, Trevor Darrell

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Deep Object-Centric Policies for Autonomous Driving.

Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell

Proceedings of the International Conference on Robotics and Automation, 2019

2018

Deep Object-Centric Representations for Generalizable Robot Learning.

Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping.

Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Learning modular neural network policies for multi-task and multi-robot transfer.

Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning.

Abhishek Gupta, Coline Devin, Yuxuan Liu, Pieter Abbeel, Sergey Levine

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints.

Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell

Proceedings of the Algorithmic Foundations of Robotics XII, 2016

2015

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments.

Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Xingchao Peng, Sergey Levine, Kate Saenko, Trevor Darrell

CoRR, 2015

Embedding Word Similarity with Neural Machine Translation.

Felix Hill, Kyunghyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio

Proceedings of the 3rd International Conference on Learning Representations, 2015

2014

Not All Neural Embeddings are Born Equal.

Felix Hill, KyungHyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio

CoRR, 2014