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Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks.

, , , , , , , , and . CVPR, page 12627-12637. Computer Vision Foundation / IEEE, (2019)

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The Principle of Unchanged Optimality in Reinforcement Learning Generalization., and . CoRR, (2019)Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?, , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 4235-4243. PMLR, (2018)Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks., , , , , , , , and . CVPR, page 12627-12637. Computer Vision Foundation / IEEE, (2019)Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?, , , , , and . CoRR, (2017)BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning., , , , , , , and . CoRR, (2022)AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale., , , , , , , , , and 1 other author(s). CoRL, volume 164 of Proceedings of Machine Learning Research, page 1078-1088. PMLR, (2021)Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping., , , , , , , , , and 2 other author(s). ICRA, page 4243-4250. IEEE, (2018)Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation., , , , , , , , , and 1 other author(s). CoRL, volume 87 of Proceedings of Machine Learning Research, page 651-673. PMLR, (2018)Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks., , , , , , , , and . CoRR, (2018)QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation., , , , , , , , , and 1 other author(s). CoRR, (2018)