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Certifiable Evaluation for Autonomous Vehicle Perception Systems using Deep Importance Sampling (Deep IS).

, , , , , , and . ITSC, page 1736-1742. IEEE, (2022)

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On the Robustness of Safe Reinforcement Learning under Observational Perturbations., , , , , , and . CoRR, (2022)Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability., , , , , , and . CoRR, (2022)Constrained Variational Policy Optimization for Safe Reinforcement Learning., , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 13644-13668. PMLR, (2022)Will this Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora., , , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 1746-1757. Association for Computational Linguistics, (2020)Gradient Shaping for Multi-Constraint Safe Reinforcement Learning., , , , , , and . CoRR, (2023)Datasets and Benchmarks for Offline Safe Reinforcement Learning., , , , , , , , , and 1 other author(s). CoRR, (2023)Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling., , , , , , and . CoRR, (2022)Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning., , , , , , and . CoRR, (2023)Learning from Sparse Offline Datasets via Conservative Density Estimation., , , , , and . CoRR, (2024)Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder., , , and . ITSC, page 3514-3519. IEEE, (2019)