Held, David

Towards fully autonomous driving: Systems and algorithms

Levinson, J., Askeland, J., Becker, J., Dolson, J., Held, D., Kammel, S., Kolter, J. Z., Langer, D., Pink, O., Pratt, V., et al. (2011) · 2011 IEEE Intelligent Vehicles Symposium (IV)

Autonomous Vehicle Technology and SafetyRobotics and Sensor-Based Localization

Cited by 1,374

Learning to Track at 100 FPS with Deep Regression Networks

Held, D., Thrun, S., & Savarese, S. (2016) · Lecture Notes in Computer Science

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,199

Constrained Policy Optimization

Achiam, J., Held, D., Tamar, A., & Abbeel, P. (2017) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 804

SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation

Lin, X., Wang, Y., Olkin, J., & Held, D. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 140

Learning Visible Connectivity Dynamics for Cloth Smoothing

Lin, X., Wang, Y., Huang, Z., & Held, D. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 62

FabricFlowNet: Bimanual Cloth Manipulation with a Flow-based Policy

Weng, T., Bajracharya, S., Wang, Y., Agrawal, K., & Held, D. (2021) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 48

Mesh-based Dynamics with Occlusion Reasoning for Cloth Manipulation

Huang, Z., Lin, X., & Held, D. (2022) · Robotics: Science and Systems XVIII

Robot Manipulation and Learning3D Shape Modeling and Analysis

Cited by 39

RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation

Wang, Y., Xian, Z., Chen, F., Wang, T.-H., Wang, Y., Fragkiadaki, K., Erickson, Z., Held, D., & Gan, C. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 15