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[1] Christopher De Sa,et al. Neural Manifold Ordinary Differential Equations , 2020, NeurIPS.
[2] Shakir Mohamed,et al. Normalizing Flows on Riemannian Manifolds , 2016, ArXiv.
[3] Iain Murray,et al. Neural Spline Flows , 2019, NeurIPS.
[4] Stefan Schaal,et al. Online movement adaptation based on previous sensor experiences , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[5] Aude Billard,et al. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models , 2011, IEEE Transactions on Robotics.
[6] Klaus Neumann,et al. Learning robot motions with stable dynamical systems under diffeomorphic transformations , 2015, Robotics Auton. Syst..
[7] Iain Murray,et al. Masked Autoregressive Flow for Density Estimation , 2017, NIPS.
[8] J.S. Yuan,et al. Closed-loop manipulator control using quaternion feedback , 1988, IEEE J. Robotics Autom..
[9] Darwin G. Caldwell,et al. An Approach for Imitation Learning on Riemannian Manifolds , 2017, IEEE Robotics and Automation Letters.
[10] Byron Boots,et al. Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems , 2020, L4DC.
[11] Nicolas Perrin,et al. Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems , 2016, Syst. Control. Lett..
[12] Hugo Larochelle,et al. MADE: Masked Autoencoder for Distribution Estimation , 2015, ICML.
[13] Gurtej Kanwar,et al. Normalizing Flows on Tori and Spheres , 2020, ICML.
[14] John M. Lee. Introduction to Smooth Manifolds , 2002 .
[15] Sandra Hirche,et al. Learning Stable Stochastic Nonlinear Dynamical Systems , 2017, ICML.
[16] Jun Morimoto,et al. Orientation in Cartesian space dynamic movement primitives , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[17] Darwin G. Caldwell,et al. Toward Orientation Learning and Adaptation in Cartesian Space , 2019, IEEE Transactions on Robotics.
[18] Stefan Schaal,et al. Learning from Demonstration , 1996, NIPS.
[19] Pieter Abbeel,et al. Apprenticeship learning via inverse reinforcement learning , 2004, ICML.
[20] João Silvério,et al. Fourier movement primitives: an approach for learning rhythmic robot skills from demonstrations , 2020, Robotics: Science and Systems.
[21] S. Schaal. Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics , 2006 .
[22] Dinesh Atchuthan,et al. A micro Lie theory for state estimation in robotics , 2018, ArXiv.
[23] Auke Jan Ijspeert,et al. Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.
[24] Patrick Forré,et al. Reparameterizing Distributions on Lie Groups , 2019, AISTATS.
[25] Daniel Kappler,et al. Riemannian Motion Policies , 2018, ArXiv.
[26] Samy Bengio,et al. Density estimation using Real NVP , 2016, ICLR.
[27] Jan Peters,et al. Probabilistic Movement Primitives , 2013, NIPS.
[28] Maximilian Nickel,et al. Riemannian Continuous Normalizing Flows , 2020, NeurIPS.
[29] David Duvenaud,et al. FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models , 2018, ICLR.
[30] Zoe Doulgeri,et al. A correct formulation for the Orientation Dynamic Movement Primitives for robot control in the Cartesian space , 2019, CoRL.
[31] Darwin G. Caldwell,et al. Kernelized movement primitives , 2017, Int. J. Robotics Res..
[32] Sylvain Calinon,et al. A tutorial on task-parameterized movement learning and retrieval , 2016, Intell. Serv. Robotics.
[33] Thomas Müller,et al. Neural Importance Sampling , 2018, ACM Trans. Graph..
[34] Klaus Neumann,et al. Neural learning of stable dynamical systems based on data-driven Lyapunov candidates , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[35] Steven M. LaValle,et al. RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[36] Jan Peters,et al. ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[37] David Duvenaud,et al. Neural Ordinary Differential Equations , 2018, NeurIPS.
[38] Oussama Khatib,et al. A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..