Dongkun Zhang

Generating author description...

All published works

Action	Title	Year	Authors
+ PDF Chat	A Two-Stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System	2023	Jintao Xue Dongkun Zhang Rong Xiong Yue Wang Eryun Liu
+	Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow	2023	Dongkun Zhang Jintao Xue Yuxiang Cui Yunkai Wang Eryun Liu Wei Jing Junbo Chen Rong Xiong Yue Wang
+	A Two-stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System	2023	Jintao Xue Dongkun Zhang Rong Xiong Yue Wang Eryun Liu
+ PDF Chat	Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation	2022	Yuxiang Cui Longzhong Lin Xiaolong Huang Dongkun Zhang Yunkai Wang Wei Jing Junbo Chen Rong Xiong Yue Wang
+ PDF Chat	Domain Generalization for Vision-based Driving Trajectory Generation	2022	Yunkai Wang Dongkun Zhang Yuxiang Cui Zexi Chen Jing Wei Junbo Chen Rong Xiong Yue Wang
+ PDF Chat	Imitation Learning of Hierarchical Driving Model: From Continuous Intention to Continuous Trajectory	2021	Yunkai Wang Dongkun Zhang Jingke Wang Zexi Chen Yuehua Li Yue Wang Rong Xiong
+	Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation	2021	Yuxiang Cui Longzhong Lin Xiaolong Huang Dongkun Zhang Yue Wang Rong Xiong
+	Domain Generalization for Vision-based Driving Trajectory Generation	2021	Yunkai Wang Dongkun Zhang Yuxiang Cui Zexi Chen Wei Jing Junbo Chen Rong Xiong Yue Wang
+ PDF Chat	Learning hierarchical behavior and motion planning for autonomous driving	2020	Jingke Wang Yue Wang Dongkun Zhang Yezhou Yang Rong Xiong
+ PDF Chat	PPINN: Parareal physics-informed neural network for time-dependent PDEs	2020	Xuhui Meng Zhen Li Dongkun Zhang George Em Karniadakis
+	Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations	2020	Liu Yang Dongkun Zhang George Em Karniadakis
+	Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks	2020	Dongkun Zhang Ling Guo George Em Karniadakis
+	Learning hierarchical behavior and motion planning for autonomous driving	2020	Jingke Wang Yue Wang Dongkun Zhang Yezhou Yang Rong Xiong
+	Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory	2020	Yunkai Wang Dongkun Zhang Jingke Wang Zexi Chen Yue Wang Rong Xiong
+	Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems	2019	Dongkun Zhang Lu Lu Ling Guo George Em Karniadakis
+	Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks	2019	Dongkun Zhang Ling Guo George Em Karniadakis
+ PDF Chat	An atomistic fingerprint algorithm for learning <i>ab initio</i> molecular force fields	2018	Yu-Hang Tang Dongkun Zhang George Em Karniadakis
+	Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations	2018	Liu Yang Dongkun Zhang George Em Karniadakis

Common Coauthors

Coauthor	Papers Together
Rong Xiong	11
Yue Wang	8
George Em Karniadakis	6
Yuxiang Cui	5
Yunkai Wang	5
Zexi Chen	4
Jingke Wang	4
Ling Guo	3
Eryun Liu	3
Jintao Xue	2
Longzhong Lin	2
Wei Jing	2
Liu Yang	2
Yezhou Yang	2
Yue Wang	1
Yue Wang	1
Yu-Hang Tang	1
Junbo Chen	1
Junbo Chen	1
Junbo Chen	1
George Em Karniadakis	1
Xiaolong Huang	1
Zhen Li	1
Jintao Xue	1
Xiaolong Huang	1
Yunkai Wang	1
Xuhui Meng	1
Wei Jing	1
Junbo Chen	1
Yuehua Li	1
Jing Wei	1
Lu Lu	1
Yue Wang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Hidden physics models: Machine learning of nonlinear partial differential equations	2017	Maziar Raissi George Em Karniadakis	5
+	Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems	2019	Dongkun Zhang Lu Lu Ling Guo George Em Karniadakis	5
+ PDF Chat	Exploring the Limitations of Behavior Cloning for Autonomous Driving	2019	Felipe Codevilla Eder Santana Antonio M. López Adrien Gaidon	4
+	Rethinking Self-driving: Multi-task Knowledge for Better Generalization and Accident Explanation Ability	2018	Zhihao Li T. Motoyoshi Kazuma Sasaki Tetsuya Ogata Shigeki Sugano	4
+ PDF Chat	End-to-End Driving Via Conditional Imitation Learning	2018	Felipe Codevilla Matthias Müller Antonio M. López Vladlen Koltun Alexey Dosovitskiy	4
+ PDF Chat	A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles	2016	B. Paden Michal Čáp Sze Zheng Yong Dmitry Yershov Emilio Frazzoli	4
+ PDF Chat	CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving	2018	Xiaodan Liang Tairui Wang Luona Yang Eric P. Xing	4
+	Baidu Apollo EM Motion Planner	2018	Haoyang Fan Fan Zhu Changchun Liu Liangliang Zhang Zhuang Li Dong Li Weicheng Zhu Jiangtao Hu Hongye Li Qi Kong	4
+ PDF Chat	DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving	2015	Chenyi Chen Ari Seff Alain L. Kornhauser Jianxiong Xiao	4
+	End to End Learning for Self-Driving Cars	2016	Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D. Jackel Mathew Monfort Urs Müller Jiakai Zhang	4
+ PDF Chat	The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset	2020	Dan Barnes Matthew Gadd Paul Murcutt Paul Newman Ingmar Posner	3
+ PDF Chat	Inverse problems: A Bayesian perspective	2010	Andrew M. Stuart	3
+ PDF Chat	Artificial neural networks for solving ordinary and partial differential equations	1998	I.E. Lagaris Aristidis Likas D.I. Fotiadis	3
+ PDF Chat	Neural-net-induced Gaussian process regression for function approximation and PDE solution	2019	Guofei Pang Liu Yang George Em Karniadakis	3
+	Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations	2017	Maziar Raissi Paris Perdikaris George Em Karniadakis	3
+	CARLA: An Open Urban Driving Simulator	2017	Alexey Dosovitskiy Germán Ros Felipe Codevilla Antonio M. López Vladlen Koltun	3
+ PDF Chat	Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations	2018	Maziar Raissi Paris Perdikaris George Em Karniadakis	3
+ PDF Chat	Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification	2018	Yinhao Zhu Nicholas Zabaras	3
+ PDF Chat	Machine learning of linear differential equations using Gaussian processes	2017	Maziar Raissi Paris Perdikaris George Em Karniadakis	3
+ PDF Chat	Forward–Backward Stochastic Neural Networks: Deep Learning of High-Dimensional Partial Differential Equations	2023	Maziar Raissi	3
+ PDF Chat	VTGNet: A Vision-Based Trajectory Generation Network for Autonomous Vehicles in Urban Environments	2020	Peide Cai Yuxiang Sun Hengli Wang Ming Liu	3
+ PDF Chat	Résolution d'EDP par un schéma en temps «pararéel »	2001	J. L. Lions Yvon Maday Gabriel Turinici	2
+ PDF Chat	Deep Reinforcement Learning framework for Autonomous Driving	2017	Ahmad El Sallab Mohammed Abdou Etienne Pérot Senthil Yogamani	2
+ PDF Chat	Deep learning of vortex-induced vibrations	2018	Maziar Raissi Zhicheng Wang Michael S. Triantafyllou George Em Karniadakis	2
+ PDF Chat	DeepGoal: Learning to drive with driving intention from human control demonstration	2020	Huifang Ma Yue Wang Rong Xiong Sarath Kodagoda Li Tang	2
+	End-to-End Deep Reinforcement Learning for Lane Keeping Assist	2016	Ahmad El Sallab Mohammed Abdou Etienne Pérot Senthil Yogamani	2
+ PDF Chat	Solving parametric PDE problems with artificial neural networks	2020	Yuehaw Khoo Jianfeng Lu Lexing Ying	2
+	High-Order Collocation Methods for Differential Equations with Random Inputs	2005	Dongbin Xiu Jan S. Hesthaven	2
+ PDF Chat	End-to-End Learning of Driving Models from Large-Scale Video Datasets	2017	Huazhe Xu Yang Gao Fisher Yu Trevor Darrell	2
+	LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning.	2019	Albert Zhao Tong He Yitao Liang Haibin Huang Guy Van den Broeck Stefano Soatto	2
+ PDF Chat	A Survey of Deep Learning Applications to Autonomous Vehicle Control	2020	Sampo Kuutti Richard Bowden Yaochu Jin Phil Barber Saber Fallah	2
+ PDF Chat	Imitation Learning of Hierarchical Driving Model: From Continuous Intention to Continuous Trajectory	2021	Yunkai Wang Dongkun Zhang Jingke Wang Zexi Chen Yuehua Li Yue Wang Rong Xiong	2
+ PDF Chat	Safe Trajectory Generation for Complex Urban Environments Using Spatio-Temporal Semantic Corridor	2019	Wenchao Ding Lu Zhang Jing Chen Shaojie Shen	2
+	TensorFlow: A system for large-scale machine learning	2016	Martı́n Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jay B. Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard	2
+ PDF Chat	Find your own way: Weakly-supervised segmentation of path proposals for urban autonomy	2017	Dan Barnes Will Maddern Ingmar Posner	2
+	Playing Atari Games with Deep Reinforcement Learning and Human Checkpoint Replay	2016	Ionel-Alexandru Hosu Traian Rebedea	2
+	Physics-Informed Kriging: A Physics-Informed Gaussian Process Regression Method for Data-Model Convergence.	2018	Xiu Yang G. Tartakovsky Alexandre M. Tartakovsky	2
+ PDF Chat	Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning	2018	David Isele Reza Rahimi Akansel Cosgun K.A. Subramanian Kikuo Fujimura	2
+	Probabilistic solvers for partial differential equations	2016	Ilias Bilionis	2
+	Agile Autonomous Driving using End-to-End Deep Imitation Learning	2018	Yunpeng Pan Ching-An Cheng Kamil Saigol Keuntaek Lee Xinyan Yan Evangelos A. Theodorou Byron Boots	2
+	Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm	2017	David Silver Thomas Hubert Julian Schrittwieser Ioannis Antonoglou Matthew Lai Arthur Guez Marc Lanctot Laurent Sifre Dharshan Kumaran Thore Graepel	2
+	Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making	2018	Jingchu Liu Pengfei Hou Lisen Mu Yinan Yu Chang Huang	2
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	2
+	Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations	2018	Liu Yang Dongkun Zhang George Em Karniadakis	2
+	Discovering governing equations from data by sparse identification of nonlinear dynamical systems	2016	Steven L. Brunton Joshua L. Proctor J. Nathan Kutz	2
+	A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning	2010	Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell	2
+ PDF Chat	Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations	2017	E Weinan Jiequn Han Arnulf Jentzen	2
+ PDF Chat	HG-DAgger: Interactive Imitation Learning with Human Experts	2019	Michael A. Kelly Chelsea Sidrane Katherine Driggs-Campbell Mykel J. Kochenderfer	2
+	CARLA: An Open Urban Driving Simulator	2017	Alexey Dosovitskiy Germán Ros Felipe Codevilla Antonio M. López Vladlen Koltun	2
+ PDF Chat	Stochastic Collocation on Unstructured Multivariate Meshes	2015	Akil Narayan Tao Tang	2