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Terrain-adaptive locomotion skills using deep reinforcement learning

ACM transactions on graphics, 2016-07, Vol.35 (4), p.1-12

2016

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Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation

Journal of neuroengineering and rehabilitation, 2021-08, Vol.18 (1), p.126-126, Article 126

2021

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The intestinal microbial community dissimilarity in hepatitis B virus-related liver cirrhosis patients with and without at alcohol consumption

Gut pathogens, 2019-11, Vol.11 (1), p.58-58, Article 58

2019

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ASE: large-scale reusable adversarial skill embeddings for physically simulated characters

ACM transactions on graphics, 2022-07, Vol.41 (4), p.1-17, Article 94

2022

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Sim-to-Real Transfer of Robotic Control with Dynamics Randomization

2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, p.3803-3810

2018

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Human umbilical cord mesenchymal stem cells inhibit proliferation of hepatic stellate cells in vitro

International journal of molecular medicine, 2018-05, Vol.41 (5), p.2545-2552

2018

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Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning

2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023, p.2715-2722

2023

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Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots

2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, p.2811-2817

2021

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Bone marrow-derived mesenchymal stem cells inhibit the proliferation of hepatic stellate cells by inhibiting the transforming growth factor β pathway

Molecular medicine reports, 2015-11, Vol.12 (5), p.7227-7232

2015

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DeepMimic: example-guided deep reinforcement learning of physics-based character skills

ACM transactions on graphics, 2018-08, Vol.37 (4), p.1-14

2018

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AMP: adversarial motion priors for stylized physics-based character control

ACM transactions on graphics, 2021-08, Vol.40 (4), p.1-20, Article 144

2021

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DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning

ACM transactions on graphics, 2017-08, Vol.36 (4), p.1-13

2017

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Distribution of HCV genotypes in Chinese Han population with chronic hepatitis C

Zhejiang da xue xue bao. Journal of Zhejiang University. Medical sciences. Yi xue ban, 2015-07, Vol.44 (4), p.417-422

2015

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SFV: reinforcement learning of physical skills from videos

ACM transactions on graphics, 2018, Vol.37 (6), p.1-14

2018

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Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World

2022 International Conference on Robotics and Automation (ICRA), 2022, p.1593-1599

2022

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Dynamic terrain traversal skills using reinforcement learning

ACM transactions on graphics, 2015-08, Vol.34 (4), p.1-11

2015

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Learning Physically Simulated Tennis Skills from Broadcast Videos

ACM transactions on graphics, 2023-08, Vol.42 (4), p.1-14, Article 95

2023

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Interactive Character Control with Auto-Regressive Motion Diffusion Models

ACM transactions on graphics, 2024-07, Vol.43 (4), p.1-14, Article 143

2024

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AMP: adversarial motion priors for stylized physics-based character control

ACM transactions on graphics, 2021-08, Vol.40 (4), p.1-20

2021

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Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.13756-13766

2023

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Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022, p.25-32

2022

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Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022, p.1479-1486

2022

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Acquiring Motor Skills through Motion Imitation and Reinforcement Learning

Peng, Xue Bin

2021

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Learning locomotion skills using DeepRL: does the choice of action space matter?

Proceedings of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 2017, p.1-13

2017

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PADL: Language-Directed Physics-Based Character Control

SIGGRAPH Asia 2022 Conference Papers, 2022, p.1-9

2022

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Terrain-adaptive locomotion skills using deep reinforcement learning

Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation

The intestinal microbial community dissimilarity in hepatitis B virus-related liver cirrhosis patients with and without at alcohol consumption

ASE: large-scale reusable adversarial skill embeddings for physically simulated characters

Sim-to-Real Transfer of Robotic Control with Dynamics Randomization

Human umbilical cord mesenchymal stem cells inhibit proliferation of hepatic stellate cells in vitro

Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning

Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots

Bone marrow-derived mesenchymal stem cells inhibit the proliferation of hepatic stellate cells by inhibiting the transforming growth factor β pathway

DeepMimic: example-guided deep reinforcement learning of physics-based character skills

AMP: adversarial motion priors for stylized physics-based character control

DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning

Distribution of HCV genotypes in Chinese Han population with chronic hepatitis C

SFV: reinforcement learning of physical skills from videos

Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World

Dynamic terrain traversal skills using reinforcement learning

Learning Physically Simulated Tennis Skills from Broadcast Videos

Interactive Character Control with Auto-Regressive Motion Diffusion Models

AMP: adversarial motion priors for stylized physics-based character control

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions

Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot

Acquiring Motor Skills through Motion Imitation and Reinforcement Learning

Learning locomotion skills using DeepRL: does the choice of action space matter?

PADL: Language-Directed Physics-Based Character Control

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