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Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.

, , , , , , , and . ICRA, page 358-365. IEEE, (2017)

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Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations., , , , , , , and . CoRR, (2016)Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations., , , , , , , and . CASE, page 827-834. IEEE, (2016)Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning., , and . CoRR, (2019)Statistical data cleaning for deep learning of automation tasks from demonstrations., , , , , and . CASE, page 1142-1149. IEEE, (2017)Learning Action-based Representations Using Invariance., , , , , and . CoRR, (2024)Gaze Supervision for Mitigating Causal Confusion in Driving Agents., , , , , , and . AAMAS, page 2159-2161. ACM, (2024)Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations., , , , , , , and . ICRA, page 358-365. IEEE, (2017)Automated Discovery of Functional Actual Causes in Complex Environments., , , , , and . CoRR, (2024)Granger-Causal Hierarchical Skill Discovery., , , , and . CoRR, (2023)ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory., , , and . ICRA, page 13670-13677. IEEE, (2021)