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Dimensionality Reduction for Dynamic Movement Primitives and Application to Bimanual Manipulation of Clothes., and . IEEE Trans. Robotics, 34 (3): 602-615 (2018)Exploiting Symmetries in Reinforcement Learning of Bimanual Robotic Tasks., , and . IEEE Robotics Autom. Lett., 4 (2): 1838-1845 (2019)Task-Adaptive Robot Learning From Demonstration With Gaussian Process Models Under Replication., , , , and . IEEE Robotics Autom. Lett., 6 (2): 966-973 (2021)Heteroscedastic Gaussian Processes and Random Features: Scalable Motion Primitives with Guarantees., , , , and . CoRL, volume 229 of Proceedings of Machine Learning Research, page 3010-3029. PMLR, (2023)Demonstration-free contextualized probabilistic movement primitives, further enhanced with obstacle avoidance., and . IROS, page 3190-3195. IEEE, (2017)White Paper on Artificial Intelligence, Robotics and Data Science, , , , , , , , , and 1 other author(s). (2021)Robot motion adaptation through user intervention and reinforcement learning., , , and . Pattern Recognit. Lett., (2018)Gaussian-Process-based Robot Learning from Demonstration., , , , and . CoRR, (2020)Controlled Gaussian Process Dynamical Models with Application to Robotic Cloth Manipulation., , , and . CoRR, (2021)Model Predictive Control for Dynamic Cloth Manipulation: Parameter Learning and Experimental Validation., , , , and . CoRR, (2022)