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Riemannian Geometry as a Unifying Theory for Robot Motion Learning and Control.

, and . ISRR, volume 27 of Springer Proceedings in Advanced Robotics, page 395-403. Springer, (2022)

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Active Improvement of Control Policies with Bayesian Gaussian Mixture Model., , , and . IROS, page 5395-5401. IEEE, (2020)Unraveling the Single Tangent Space Fallacy: An Analysis and Clarification for Applying Riemannian Geometry in Robot Learning., , and . ICRA, page 242-249. IEEE, (2024)Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds., , , , and . ICML, OpenReview.net, (2024)K-VIL: Keypoints-based Visual Imitation Learning., , , and . CoRR, (2022)Gaussian mixture regression on symmetric positive definite matrices manifolds: Application to wrist motion estimation with sEMG., and . IROS, page 59-64. IEEE, (2017)Unraveling the Single Tangent Space Fallacy: An Analysis and Clarification for Applying Riemannian Geometry in Robot Learning., , and . CoRR, (2023)An Evaluation of Action Segmentation Algorithms on Bimanual Manipulation Datasets., , , and . IROS, page 4912-4919. (2023)Geometry-aware Manipulability Transfer., , , and . CoRR, (2018)Transfer Learning in Robotics: An Upcoming Breakthrough? A Review of Promises and Challenges., , , , , , , , and . CoRR, (2023)Riemann2: Learning Riemannian Submanifolds from Riemannian Data., , , and . CoRR, (March 2025)