activity
20162026
most citedTest Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling

1 citations · 5 across the 7 of their papers we have counts for

collaborators

19 papers

eess.SY2026

Hierarchical Control for Continuous-time Systems via General Approximate Alternating Simulation Relations

Zhiyuan Huang, Shuo Li, Murat Arcak +2

This paper introduces a general approximate alternating simulation relation (\emph{-gAAS relation}) for continuous-time systems, which relaxes existing simulation rela…

math.ST2023

Propagation of Input Tail Uncertainty in Rare-Event Estimation: A Light versus Heavy Tail Dichotomy

Zhiyuan Huang, Henry Lam, Zhenyuan Liu

We consider the estimation of small probabilities or other risk quantities associated with rare but catastrophic events. In the model-based literature, much of the focus has been d…

cs.LG2022★ 1 cited

Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling

Mansur Arief, Zhepeng Cen, Zhenyuan Liu +4

Evaluating the performance of autonomous vehicles (AV) and their complex subsystems to high precision under naturalistic circumstances remains a challenge, especially when failure…

stat.ME2021

Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems

Mansur Arief, Yuanlu Bai, Wenhao Ding +4

Rare-event simulation techniques, such as importance sampling (IS), constitute powerful tools to speed up challenging estimation of rare catastrophic events. These techniques often…

math.ST2021★ 1 cited

Over-Conservativeness of Variance-Based Efficiency Criteria and Probabilistic Efficiency in Rare-Event Simulation

Yuanlu Bai, Zhiyuan Huang, Henry Lam +1

In rare-event simulation, an importance sampling (IS) estimator is regarded as efficient if its relative error, namely the ratio between its standard deviation and mean, is suffici…

cs.LG2021

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling

Mengdi Xu, Peide Huang, Fengpei Li +6

Evaluating rare but high-stakes events is one of the main challenges in obtaining reliable reinforcement learning policies, especially in large or infinite state/action spaces wher…