Wenhao Ding

According to our database, Wenhao Ding authored at least 47 papers between 2018 and 2024.

Collaborative distances:

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

2024

Safety-Aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving.

Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao

IEEE Robotics Autom. Lett., May, 2024

River ecosystem health assessment in the Qinghai-Tibet Plateau: A novel hybrid method based on artificial intelligence and multi-source data fusion.

Zhengxian Zhang, Xiaogang Wang, Yun Li, Yi Liu, Yuan Xu, Jingjuan Li, Wenhao Ding, Hongze Li, Hong Yang

Expert Syst. Appl., 2024

Explicit Differentiable Slicing and Global Deformation for Cardiac Mesh Reconstruction.

Yihao Luo, Dario Sesia, Fanwen Wang, Yinzhe Wu, Wenhao Ding, Jiahao Huang, Fadong Shi, Anoop Shah, Amit Kaural, Jamil Mayet, Guang Yang, Choon Hwai Yap

CoRR, 2024

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning.

Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao

CoRR, 2024

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning.

Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao

CoRR, 2024

CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories.

Peide Huang, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao

CoRR, 2024

Privacy Risks in Reinforcement Learning for Household Robots.

Miao Li, Wenhao Ding, Ding Zhao

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios.

Wenhao Ding, Yulong Cao, Ding Zhao, Chaowei Xiao, Marco Pavone

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Loan Default Prediction Based on Convolutional Neural Network and LightGBM.

Qiliang Zhu, Wenhao Ding, Mingsen Xiang, Mengzhen Hu, Ning Zhang

Int. J. Data Warehous. Min., March, 2023

A Survey on Safety-Critical Driving Scenario Generation - A Methodological Perspective.

Wenhao Ding, Chejian Xu, Mansur Arief, Haohong Lin, Bo Li, Ding Zhao

IEEE Trans. Intell. Transp. Syst., 2023

Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving.

Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao

CoRR, 2023

Your Room is not Private: Gradient Inversion Attack for Deep Q-Learning.

Miao Li, Wenhao Ding, Ding Zhao

CoRR, 2023

Critical Scenario Generation for Developing Trustworthy Autonomy.

Wenhao Ding

CoRR, 2023

GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling.

Yiwen Dong, Yuyan Wu, Jesse R. Codling, Jatin Aggarwal, Peide Huang, Wenhao Ding, Hugo Latapie, Pei Zhang, Hae Young Noh

Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, 2023

Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation.

Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments.

Hanjiang Hu, Baoquan Yang, Zhijian Qiao, Shiqi Liu, Jiacheng Zhu, Zuxin Liu, Wenhao Ding, Ding Zhao, Hesheng Wang

IROS, 2023

Learning to View: Decision Transformers for Active Object Detection.

Wenhao Ding, Nathalie Majcherczyk, Mohit Deshpande, Xuewei Qi, Ding Zhao, Rajasimman Madhivanan, Arnie Sen

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models.

Wenhao Ding, Tong Che, Ding Zhao, Marco Pavone

Proceedings of the International Conference on Machine Learning, 2023

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery.

Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao

Proceedings of the Conference on Robot Learning, 2023

2022

Solving practical multi-body dynamics problems using a single neural operator.

Wenhao Ding, Qing He, Hanghang Tong, Qingjing Wang, Ping Wang

CoRR, 2022

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability.

Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao

CoRR, 2022

PINO-MBD: Physics-informed Neural Operator for Solving Coupled ODEs in Multi-body Dynamics.

Wenhao Ding, Qing He, Hanghang Tong, Ping Wang

CoRR, 2022

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles.

Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning.

Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation.

Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

Proceedings of the Conference on Robot Learning, 2022

2021

Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation.

Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao

IEEE Robotics Autom. Lett., 2021

CausalAF: Causal Autoregressive Flow for Goal-Directed Safety-Critical Scenes Generation.

Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

CoRR, 2021

Semantically Controllable Scene Generation with Guidance of Explicit Knowledge.

Wenhao Ding, Bo Li, Kim Ji Eun, Ding Zhao

CoRR, 2021

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments.

Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao

CoRR, 2021

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments.

Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems.

Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Adaptive Multi-Scale Detection of Acoustic Events.

Wenhao Ding, Liang He

IEEE ACM Trans. Audio Speech Lang. Process., 2020

Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy.

Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao

CoRR, 2020

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method.

Wenhao Ding, Minjun Xu, Ding Zhao

CoRR, 2020

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes.

Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method.

Wenhao Ding, Baiming Chen, Minjun Xu, Ding Zhao

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

CMTS: A Conditional Multiple Trajectory Synthesizer for Generating Safety-Critical Driving Scenarios.

Wenhao Ding, Mengdi Xu, Ding Zhao

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Adaptive Multi-scale Detection of Acoustic Events.

Wenhao Ding, Liang He

CoRR, 2019

Multi-Scale Time-Frequency Attention for Rare Sound Event Detection.

Jingyang Zhang, Wenhao Ding, Jintao Kang, Liang He

CoRR, 2019

Multi-Scale Time-Frequency Attention for Acoustic Event Detection.

Jingyang Zhang, Wenhao Ding, Jintao Kang, Liang He

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

A Multi-Vehicle Trajectories Generator to Simulate Vehicle-to-Vehicle Encountering Scenarios.

Wenhao Ding, Wenshuo Wang, Ding Zhao

Proceedings of the International Conference on Robotics and Automation, 2019

2018

Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters.

Wenhao Ding, Wenshuo Wang, Ding Zhao

CoRR, 2018

Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation.

Wenhao Ding, Shuaijun Li, Huihuan Qian

CoRR, 2018

Vehicle Three-Dimensional Pose and Shape Estimation from Multiple Monocular Vision.

Wenhao Ding, Shuaijun Li, Guilin Zhang, Xiangyu Lei, Huihuan Qian, Yangsheng Xu

CoRR, 2018

Vehicle Pose and Shape Estimation Through Multiple Monocular Vision.

Wenhao Ding, Shuaijun Li, Guilin Zhang, Xiangyu Lei, Huihuan Qian

Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2018

Hierarchical Reinforcement Learning Framework Towards Multi-Agent Navigation.

Wenhao Ding, Shuaijun Li, Huihuan Qian, Yongquan Chen

Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2018

MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks.

Wenhao Ding, Liang He

Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018