
Certifiable Accelerated Evaluation
Rigorous evaluation of intelligent physical systems against long-tail failures
M. Arief, Z. Huang, G. Kumar, Y. Bai, S. He, W. Ding, H. Lam, D. Zhao, ''Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems,'' Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021, San Diego, USA, 2021. | Bib |
F Wu, L Li, Z Huang, Y Vorobeychik, D Zhao, B Li, ''CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing,'' The International Conference on Learning Representations (ICLR), 2022. | |
Z Liu, Z Cen, V Isenbaev, W Liu, ZS Wu, B Li, D Zhao, ''Constrained variational policy optimization for safe reinforcement learning,'' Thirty-ninth International Conference on Machine Learning (ICML), 2022. | |
B. Chen, Z. Liu, J. Zhu, M. Xu, W. Ding, D. Zhao, ''Context-Aware Safe Reinforcement Learning for Non-Stationary Environments,'' 2021 International Conference on Robotics and Automation (ICRA), 2021. | Bib |
M. Xu, W. Ding, J. Zhu, Z. Liu, B. Chen, D. Zhao, ''Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes,'' Advances in Neural Information Processing Systems (NeurIPS), 2020. | Bib |
M. Xu, Y. Shen, S. Zhang, Y. Lu, D. Zhao, J, Tenenbaum, C. Gan, ''Prompting Decision Transformer for Few-shot Policy Generalization,'' Thirty-ninth International Conference on Machine Learning (ICML), 2022. | |
W. Ding, H. Lin, B. Li, D. Zhao, ''Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning,'' Advances in Neural Information Processing Systems (NeurIPS), 2022. | |
Rigorous evaluation of intelligent physical systems against long-tail failures
Use unsupervised learning, stochastic processing, and generative models to comprehend and generate naturalistic safety-critical environments
Design trustworthy intelligent autonomy for real world applications.
An open platform that facilitates development of Connected and Self-Driving Vehicles
Applications: multi-robot coordination in warehouse environment; food delivery robot on sidewalks.
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