| A survey on safety-critical driving scenario generation—A methodological perspective W Ding, C Xu, M Arief, H Lin, B Li, D Zhao IEEE T-ITS, 2023 | 326 | 2023 |
| Learning to collide: An adaptive safety-critical scenarios generating method W Ding, B Chen, M Xu, D Zhao 2020 IROS, 2020 | 172* | 2020 |
| Multimodal safety-critical scenarios generation for decision-making algorithms evaluation W Ding, B Chen, B Li, KJ Eun, D Zhao IEEE RA-L, 2021 | 142 | 2021 |
| SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles C Xu*, W Ding*, W Lyu, Z Liu, S Wang, Y He, H Hu, D Zhao, B Li 2022 NeurIPS, 2022 | 99 | 2022 |
| Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters W Ding, W Wang, D Zhao 2019 ICRA, 2018 | 91* | 2018 |
| Cmts: A conditional multiple trajectory synthesizer for generating safety-critical driving scenarios W Ding, M Xu, D Zhao 2020 ICRA, 2020 | 79 | 2020 |
| Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning W Ding, H Lin, B Li, D Zhao 2022 NeurIPS, 2022 | 70 | 2022 |
| Trustworthy reinforcement learning against intrinsic vulnerabilities: Robustness, safety, and generalizability M Xu, Z Liu, P Huang, W Ding, Z Cen, B Li, D Zhao arXiv preprint arXiv:2209.08025, 2022 | 68 | 2022 |
| CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation W Ding, H Lin, B Li, D Zhao 2022 CoRL, 2022 | 61* | 2022 |
| Context-Aware Safe Reinforcement Learning for Non-Stationary Environments B Chen, Z Liu, J Zhu, M Xu, W Ding, D Zhao 2021 ICRA, 2021 | 57 | 2021 |
| What went wrong? closing the sim-to-real gap via differentiable causal discovery P Huang, X Zhang, Z Cao, S Liu, M Xu, W Ding, J Francis, B Chen, ... 2023 CoRL, 2023 | 53 | 2023 |
| Realgen: Retrieval augmented generation for controllable traffic scenarios W Ding, Y Cao, D Zhao, C Xiao, M Pavone 2024 ECCV, 2024 | 52 | 2024 |
| Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation W Ding, S Li, H Qian 2018 ROBIO, 2018 | 51 | 2018 |
| Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation W Ding*, L Shi*, Y Chi, D Zhao 2023 NeurIPS, 2023 | 50 | 2023 |
| Vehicle Pose and Shape Estimation through Multiple Monocular Vision W Ding, S Li, G Zhang, X Lei, H Qian 2018 ROBIO, 2018 | 50 | 2018 |
| Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems M Arief, Z Huang, GKS Kumar, Y Bai, S He, W Ding, H Lam, D Zhao 2021 AISTATS, 2021 | 49* | 2021 |
| Task-agnostic online reinforcement learning with an infinite mixture of gaussian processes M Xu, W Ding, J Zhu, Z Liu, B Chen, D Zhao 2020 NeurIPS, 2020 | 49 | 2020 |
| Certifiable deep importance sampling for rare-event simulation of black-box systems M Arief, Y Bai, W Ding, S He, Z Huang, H Lam, D Zhao arXiv preprint arXiv:2111.02204, 2021 | 41* | 2021 |
| Data Augmentation and Prior Knowledge-based Regularization for Sound Event Localization and Detection W Ding*, J Zhang*, L He DCASE 2019 Task 3 Report, 2019 | 39 | 2019 |
| Semantically controllable scene generation with guidance of explicit knowledge W Ding, B Li, KJ Eun, D Zhao IEEE T-ITS, 2025 | 35* | 2025 |
Bo LiUniversity of Illinois at Urbana–ChampaignVerified email at illinois.edu
