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MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale


Apr 27, 2021
Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar, Benjamin Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, Karol Hausman


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Adaptive Intermediate Representations for Video Understanding


Apr 14, 2021
Juhana Kangaspunta, AJ Piergiovanni, Rico Jonschkowski, Michael Ryoo, Anelia Angelova


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The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels


Jan 07, 2021
Austin Stone, Oscar Ramirez, Kurt Konolige, Rico Jonschkowski

* Code available at https://github.com/google-research/google-research/tree/master/distracting_control 

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Learning Object-Centric Video Models by Contrasting Sets


Nov 20, 2020
Sindy Löwe, Klaus Greff, Rico Jonschkowski, Alexey Dosovitskiy, Thomas Kipf

* NeurIPS 2020 Workshop on Object Representations for Learning and Reasoning 

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A Geometric Perspective on Self-Supervised Policy Adaptation


Nov 14, 2020
Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski

* Contains 17 pages, 18 figures 

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What Matters in Unsupervised Optical Flow


Jun 08, 2020
Rico Jonschkowski, Austin Stone, Jonathan T. Barron, Ariel Gordon, Kurt Konolige, Anelia Angelova

* Source code is available at https://github.com/google-research/google-research/tree/master/uflow 

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Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization


May 19, 2020
Peter Karkus, Anelia Angelova, Vincent Vanhoucke, Rico Jonschkowski

* ICRA 2020 

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Towards Differentiable Resampling


Apr 24, 2020
Michael Zhu, Kevin Murphy, Rico Jonschkowski


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KeyPose: Multi-view 3D Labeling and Keypoint Estimation for Transparent Objects


Dec 05, 2019
Xingyu Liu, Rico Jonschkowski, Anelia Angelova, Kurt Konolige


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Towards Object Detection from Motion


Sep 17, 2019
Rico Jonschkowski, Austin Stone


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Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras


Apr 10, 2019
Ariel Gordon, Hanhan Li, Rico Jonschkowski, Anelia Angelova


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Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors


May 30, 2018
Rico Jonschkowski, Divyam Rastogi, Oliver Brock

* Accepted at Robotics: Science and Systems 2018 (http://www.roboticsconference.org

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PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations


Jul 24, 2017
Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin Riedmiller

* Accepted at Robotics: Science and Systems (RSS 2017) Workshop -- New Frontiers for Deep Learning in Robotics http://juxi.net/workshop/deep-learning-rss-2017/ 

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Patterns for Learning with Side Information


Feb 10, 2016
Rico Jonschkowski, Sebastian Höfer, Oliver Brock

* The first two authors contributed equally to this work 

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