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Learning Riemannian Manifolds for Geodesic Motion Skills.

, , , , и . Robotics: Science and Systems, (2021)

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Carl-Fredrik Sørensen

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Jørgen Skov Sørensen

Jost Hauberg

Gustav Hauberg

 

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Three Dimensional Monocular Human Motion Analysis in End-Effector Space., , , , и . EMMCVPR, том 5681 из Lecture Notes in Computer Science, стр. 235-248. Springer, (2009)What is a meaningful representation of protein sequences?, , и . CoRR, (2020)Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry., , , и . CoG, стр. 385-392. IEEE, (2022)Adaptive Cholesky Gaussian Processes., , , , , и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 408-452. PMLR, (2023)A Locally Adaptive Normal Distribution., , и . NIPS, стр. 4251-4259. (2016)Bounds all around: training energy-based models with bidirectional bounds., , , , и . NeurIPS, стр. 19808-19821. (2021)Revisiting Active Sets for Gaussian Process Decoders., , и . NeurIPS, (2022)Spontaneous Symmetry Breaking in Data Visualization., , и . ICANN (2), том 12892 из Lecture Notes in Computer Science, стр. 435-446. Springer, (2021)Neural Contractive Dynamical Systems., , , , , и . ICLR, OpenReview.net, (2024)Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 2368-2377. PMLR, (2019)