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Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data., , , , , , , и . ICRA, стр. 9411-9418. IEEE, (2020)ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions., , , , , и . CoRR, (2020)SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards., , , , , , и . WAFR, том 13 из Springer Proceedings in Advanced Robotics, стр. 672-687. Springer, (2016)Disentangling Dense Multi-Cable Knots., , , , , , , , , и . IROS, стр. 3731-3738. IEEE, (2021)Safe Reinforcement Learning Using Learned Safe Sets. University of California, Berkeley, USA, (2022)Untangling Dense Knots by Learning Task-Relevant Keypoints., , , , , , , , , и . CoRR, (2020)Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies., , , , , , , , , и . Robotics: Science and Systems, (2021)Learning to Localize, Grasp, and Hand Over Unmodified Surgical Needles., , , , , , , и . ICRA, стр. 9637-9643. IEEE, (2022)Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics., , , , , , , , , и 3 other автор(ы). ICRA, стр. 11515-11522. IEEE, (2021)Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism., , , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 10236-10246. PMLR, (2021)