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Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost., , , , and . CoRR, (2018)Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations., , , , , and . CoRR, (2017)Fast, strong and compliant pneumatic actuation for dexterous tendon-driven hands., , and . ICRA, page 1512-1519. IEEE, (2013)Learning Deep Visuomotor Policies for Dexterous Hand Manipulation., , , , , and . ICRA, page 3636-3643. IEEE, (2019)Zero-Shot Robot Manipulation from Passive Human Videos., , , and . CoRR, (2023)MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand., , , , , , , , , and 19 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 233-250. PMLR, (2021)RoboHive: A Unified Framework for Robot Learning., , , , , , , and . CoRR, (2023)VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training., , , , , and . ICLR, OpenReview.net, (2023)CoNMix for Source-free Single and Multi-target Domain Adaptation., , , and . WACV, page 4167-4177. IEEE, (2023)Motivating the Use of Machine-Learning for Improving Timing Behaviour of Embedded Mixed-Criticality Systems., , and . DATE, page 1-2. IEEE, (2024)