MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks. - Wenhao Ding; Liang He 003 (INTERSPEECH, 2018)

Hierarchical Reinforcement Learning Framework Towards Multi-Agent Navigation. - Wenhao Ding; Shuaijun Li; Huihuan Qian; Yongquan Chen (ROBIO, 2018)

Vehicle Pose and Shape Estimation Through Multiple Monocular Vision. - Wenhao Ding; Shuaijun Li; Guilin Zhang; Xiangyu Lei; Huihuan Qian (ROBIO, 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)

MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks. - Wenhao Ding; Liang He (CoRR, 2018)

Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation. - Wenhao Ding; Shuaijun Li; Huihuan Qian (CoRR, 2018)

Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters. - Wenhao Ding; Wenshuo Wang 001; Ding Zhao (CoRR, 2018)

A Multi-Vehicle Trajectories Generator to Simulate Vehicle-to-Vehicle Encountering Scenarios. - Wenhao Ding; Wenshuo Wang 001; Ding Zhao (ICRA, 2019)

Multi-Scale Time-Frequency Attention for Acoustic Event Detection. - Jingyang Zhang; Wenhao Ding; Jintao Kang; Liang He 003 (INTERSPEECH, 2019)

Multi-Scale Time-Frequency Attention for Rare Sound Event Detection. - Jingyang Zhang; Wenhao Ding; Jintao Kang; Liang He (CoRR, 2019)

Adaptive Multi-scale Detection of Acoustic Events. - Wenhao Ding; Liang He (CoRR, 2019)

CMTS: A Conditional Multiple Trajectory Synthesizer for Generating Safety-Critical Driving Scenarios. - Wenhao Ding; Mengdi Xu; Ding Zhao (ICRA, 2020)

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. - Wenhao Ding; Baiming Chen; Minjun Xu; Ding Zhao (IROS, 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 (NeurIPS, 2020)

Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. - Wenhao Ding; Minjun Xu; Ding Zhao (CoRR, 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)

Adaptive Multi-Scale Detection of Acoustic Events. - Wenhao Ding; Liang He 003 (IEEE ACM Trans. Audio Speech Lang. Process., 2020)

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 (AISTATS, 2021)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Liang Li 004; Ding Zhao (ICRA, 2021)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Ding Zhao (CoRR, 2021)

Semantically Controllable Scene Generation with Guidance of Explicit Knowledge. - Wenhao Ding; Bo Li 026; Kim Ji Eun; Ding Zhao (CoRR, 2021)

CausalAF: Causal Autoregressive Flow for Goal-Directed Safety-Critical Scenes Generation. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (CoRR, 2021)

Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation. - Wenhao Ding; Baiming Chen; Bo Li 026; Kim Ji Eun; Ding Zhao (IEEE Robotics Autom. Lett., 2021)

CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (CoRL, 2022)

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (NeurIPS, 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 026 (NeurIPS, 2022)

PINO-MBD: Physics-informed Neural Operator for Solving Coupled ODEs in Multi-body Dynamics. - Wenhao Ding; Qing He 011; Hanghang Tong; Ping Wang 077 (CoRR, 2022)

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. - Mengdi Xu; Zuxin Liu; Peide Huang; Wenhao Ding; Zhepeng Cen; Bo Li 026; Ding Zhao (CoRR, 2022)

Solving practical multi-body dynamics problems using a single neural operator. - Wenhao Ding; Qing He 011; Hanghang Tong; Qingjing Wang; Ping Wang 077 (CoRR, 2022)

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. - Peide Huang; Xilun Zhang; Ziang Cao; Shiqi Liu 005; Mengdi Xu; Wenhao Ding; Jonathan Francis; Bingqing Chen; Ding Zhao (CoRL, 2023)

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models. - Wenhao Ding; Tong Che; Ding Zhao; Marco Pavone 001 (ICML, 2023)

Learning to View: Decision Transformers for Active Object Detection. - Wenhao Ding; Nathalie Majcherczyk; Mohit Deshpande; Xuewei Qi; Ding Zhao; Rajasimman Madhivanan; Arnie Sen (ICRA, 2023)

SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments. - Hanjiang Hu; Baoquan Yang; Zhijian Qiao; Shiqi Liu 005; Jiacheng Zhu; Zuxin Liu; Wenhao Ding; Ding Zhao; Hesheng Wang 001 (IROS, 2023)

Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. - Wenhao Ding; Laixi Shi; Yuejie Chi; Ding Zhao (NeurIPS, 2023)

GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling. - Yiwen Dong 001; Yuyan Wu; Jesse R. Codling; Jatin Aggarwal; Peide Huang; Wenhao Ding; Hugo Latapie; Pei Zhang 001; Hae Young Noh (BuildSys, 2023)

Critical Scenario Generation for Developing Trustworthy Autonomy. - Wenhao Ding (CoRR, 2023)

Your Room is not Private: Gradient Inversion Attack for Deep Q-Learning. - Miao Li; Wenhao Ding; Ding Zhao (CoRR, 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)

A Survey on Safety-Critical Driving Scenario Generation - A Methodological Perspective. - Wenhao Ding; Chejian Xu; Mansur Arief; Haohong Lin; Bo Li 026; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 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., 2023)

RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios. - Wenhao Ding; Yulong Cao; Ding Zhao; Chaowei Xiao; Marco Pavone 001 (ECCV (62), 2024)

Privacy Risks in Reinforcement Learning for Household Robots. - Miao Li; Wenhao Ding; Ding Zhao (ICRA, 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 (NeurIPS, 2024)

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning. - Yihang Yao; Zhepeng Cen; Wenhao Ding; Haohong Lin; Shiqi Liu 005; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (NeurIPS, 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)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Haohong Lin; Wenhao Ding; Jian Chen; Laixi Shi; Jiacheng Zhu; Bo Li 026; Ding Zhao (CoRR, 2024)

Explicit Differentiable Slicing and Global Deformation for Cardiac Mesh Reconstruction. - Yihao Luo; Dario Sesia; Fanwen Wang; Yinzhe Wu 001; Wenhao Ding; Jiahao Huang; Fadong Shi; Anoop Shah; Amit Kaural; Jamil Mayet; Guang Yang 006; Choon Hwai Yap (CoRR, 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)

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., 2024)

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning. - Yiwen Dong 001; Sung Eun Kim; Kornel Schadl; Peide Huang; Wenhao Ding; Jessica Rose; Hae Young Noh (IEEE J. Biomed. Health Informatics, 2024)

Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models. - Zhejun Zhang; Péter Karkus; Maximilian Igl; Wenhao Ding; Yuxiao Chen 008; Boris Ivanovic; Marco Pavone 001 (CVPR, 2025)

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network. - Wei Xuan Chan; Wenhao Ding; Bing Huan Li; Hong Shen Wong; Choon Hwai Yap (Comput. Biol. Medicine, 2025)

An improved model for time-varying mesh stiffness of super-high-contact-ratio helical gear pair considering contact disparities on differently sliced fractal surfaces. - Guodong Zhu; Kang Huang; Yangshou Xiong; Anqi Li; Jiyou Peng; Wenhao Ding (Commun. Nonlinear Sci. Numer. Simul., 2025)

Surprise Potential as a Measure of Interactivity in Driving Scenarios. - Wenhao Ding; Sushant Veer; Karen Leung; Yulong Cao; Marco Pavone 001 (CoRR, 2025)

Semantically Adversarial Scene Generation With Explicit Knowledge Guidance. - Wenhao Ding; Haohong Lin; Bo Li 026; Ding Zhao (IEEE Trans. Intell. Transp. Syst., 2025)

Deployable and Generalizable Motion Prediction: Taxonomy, Open Challenges and Future Directions. - Letian Wang; Marc-Antoine Lavoie; Sandro Papais; Barza Nisar; Yuxiao Chen 008; Wenhao Ding; Boris Ivanovic; Hao Shao; Abulikemu Abuduweili; Evan Cook; Yang Zhou 019; Péter Karkus; et al. (CoRR, 2025)

Two-Stage Generative Model for Intracranial Aneurysm Meshes with Morphological Marker Conditioning. - Wenhao Ding; Choon Hwai Yap; Kangjun Ji; Simão Castro (CoRR, 2025)

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning. - Miao Li; Wenhao Ding; Haohong Lin; Yiqi Lyu; Yihang Yao; Yuyou Zhang; Ding Zhao (CoRR, 2025)

RealDrive: Retrieval-Augmented Driving with Diffusion Models. - Wenhao Ding; Sushant Veer; Yuxiao Chen 008; Yulong Cao; Chaowei Xiao; Marco Pavone 001 (CoRR, 2025)

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning. - Yiqing Liang; Jielin Qiu; Wenhao Ding; Zuxin Liu; James Tompkin 001; Mengdi Xu; Mengzhou Xia; Zhengzhong Tu; Laixi Shi; Jiacheng Zhu (CoRR, 2025)

Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators. - Kaustav Chakraborty; Zeyuan Feng; Sushant Veer; Apoorva Sharma; Wenhao Ding; Sever Topan; Boris Ivanovic; Marco Pavone 001; Somil Bansal (CoRR, 2025)