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Ge Li (Bruce)
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Specializing versatile skill libraries using local mixture of experts
O Celik, D Zhou, G Li, P Becker, G Neumann
Conference on Robot Learning, 1423-1433, 2022
282022
Prodmp: A unified perspective on dynamic and probabilistic movement primitives
G Li, Z Jin, M Volpp, F Otto, R Lioutikov, G Neumann
IEEE Robotics and Automation Letters 8 (4), 2325-2332, 2023
232023
Evaluation of CFD predictions using different turbulence models on a film cooled guide vane under experimental conditions
Q Zhang, H Xu, J Wang, G Li, L Wang, X Wu, S Ma
Turbo Expo: Power for Land, Sea, and Air 56710, V05AT10A010, 2015
132015
Numerical investigation on aerodynamic drag and noise of pantographs with modified structures
Y Yao, Z Sun, G Li, P Prapamonthon, G Cheng, G Yang
Journal of Applied Fluid Mechanics 15 (2), 617-631, 2022
52022
Mp3: Movement primitive-based (re-) planning policy
F Otto, H Zhou, O Celik, G Li, R Lioutikov, G Neumann
arXiv preprint arXiv:2306.12729, 2023
42023
Predicting adiabatic film effectiveness of a turbine vane by two-equation turbulence models
P Prapamonthon, H Xu, J Wang, G Li
Turbo Expo: Power for Land, Sea, and Air 56727, V05BT12A019, 2015
32015
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
G Li, H Zhou, D Roth, S Thilges, F Otto, R Lioutikov, G Neumann
The Twelfth International Conference on Learning Representations, 2024
12024
MP3: Movement Primitive-Based (Re-) Planning Policy
H Zhou, F Otto, O Celik, G Li, R Lioutikov, G Neumann
CoRL 2023 Workshop on Learning Effective Abstractions for Planning (LEAP), 2023
2023
An Encoder-Decoder Architecture for Smooth Motion Generation
Z Lončarević, G Li, G Neumann, A Gams
International Conference on Robotics in Alpe-Adria Danube Region, 358-366, 2023
2023
Latent Space Exploration and Trajectory Space Update in Temporally-Correlated Episodic Reinforcement Learning
G Li, H Zhou, D Roth, S Thilges, F Otto, R Lioutikov, G Neumann
ICRA 2024 Workshop {\textemdash} Back to the Future: Robot Learning Going …, 0
Solving Real-World Robot Manip-ulation Tasks with Deep Rein-forcement Learning
TTPR Lioutikov, H Zhou, G Li
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