Dongkun Zhang

According to our database, Dongkun Zhang authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Enhancing Closed-Loop Performance in Learning-Based Vehicle Motion Planning by Integrating Rule-Based Insights.

Yunkai Wang, Quyu Kong, He Zhu, Dongkun Zhang, Longzhong Lin, Hao Sha, Xunlong Xia, Qiao Liang, Bing Deng, Ken Chen, Rong Xiong, Yue Wang, Jieping Ye

IEEE Robotics Autom. Lett., September, 2024

2023

Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow.

Dongkun Zhang, Jintao Xue, Yuxiang Cui, Yunkai Wang, Eryun Liu, Wei Jing, Junbo Chen, Rong Xiong, Yue Wang

CoRR, 2023

A Two-Stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System.

Jintao Xue, Dongkun Zhang, Rong Xiong, Yue Wang, Eryun Liu

IROS, 2023

2022

Domain Generalization for Vision-based Driving Trajectory Generation.

Yunkai Wang, Dongkun Zhang, Yuxiang Cui, Zexi Chen, Wei Jing, Junbo Chen, Rong Xiong, Yue Wang

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation.

Yuxiang Cui, Longzhong Lin, Xiaolong Huang, Dongkun Zhang, Yunkai Wang, Wei Jing, Junbo Chen, Rong Xiong, Yue Wang

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

Imitation Learning of Hierarchical Driving Model: From Continuous Intention to Continuous Trajectory.

Yunkai Wang, Dongkun Zhang, Jingke Wang, Zexi Chen, Yuehua Li, Yue Wang, Rong Xiong

IEEE Robotics Autom. Lett., 2021

Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation.

Yuxiang Cui, Longzhong Lin, Xiaolong Huang, Dongkun Zhang, Yue Wang, Rong Xiong

CoRR, 2021

2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks.

Dongkun Zhang, Ling Guo, George Em Karniadakis

SIAM J. Sci. Comput., 2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations.

Liu Yang, Dongkun Zhang, George Em Karniadakis

SIAM J. Sci. Comput., 2020

Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory.

Yunkai Wang, Dongkun Zhang, Jingke Wang, Zexi Chen, Yue Wang, Rong Xiong

CoRR, 2020

Learning hierarchical behavior and motion planning for autonomous driving.

Jingke Wang, Yue Wang, Dongkun Zhang, Yezhou Yang, Rong Xiong

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems.

Dongkun Zhang, Lu Lu, Ling Guo, George Em Karniadakis

J. Comput. Phys., 2019

PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs.

Xuhui Meng, Zhen Li, Dongkun Zhang, George Em Karniadakis

CoRR, 2019

2018

Stochastic Domain Decomposition via Moment Minimization.

Dongkun Zhang, Hessam Babaee, George E. Karniadakis

SIAM J. Sci. Comput., 2018

Bi-directional coupling between a PDE-domain and an adjacent Data-domain equipped with multi-fidelity sensors.

Dongkun Zhang, Liu Yang, George E. Karniadakis

J. Comput. Phys., 2018

2017

An Atomistic Fingerprint Algorithm for Learning Ab Initio Molecular Force Fields.

Yu-Hang Tang, Dongkun Zhang, George E. Karniadakis

CoRR, 2017