7 citations · 7 across the 3 of their papers we have counts for
7 papers
Domain Generalization for Vision-based Driving Trajectory Generation
Yunkai Wang, Dongkun Zhang, Yuxiang Cui +5
One of the challenges in vision-based driving trajectory generation is dealing with out-of-distribution scenarios. In this paper, we propose a domain generalization method for visi…
Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation
Yuxiang Cui, Longzhong Lin, Xiaolong Huang +3
Safety is of great importance in multi-robot navigation problems. In this paper, we propose a control barrier function (CBF) based optimizer that ensures robot safety with both hig…
Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory
Yunkai Wang, Dongkun Zhang, Jingke Wang +3
One of the challenges to reduce the gap between the machine and the human level driving is how to endow the system with the learning capacity to deal with the coupled complexity of…
Learning hierarchical behavior and motion planning for autonomous driving
Jingke Wang, Yue Wang, Dongkun Zhang +2
Learning-based driving solution, a new branch for autonomous driving, is expected to simplify the modeling of driving by learning the underlying mechanisms from data. To improve th…
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
Xuhui Meng, Zhen Li, Dongkun Zhang +1
Physics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accura…
Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks
Dongkun Zhang, Ling Guo, George Em Karniadakis
One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs). We address this problem by taking adva…