457 citations · 696 across the 72 of their papers we have counts for
4 papers · 2 filters
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…
Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set
Yuanlu Bai, Tucker Balch, Haoxian Chen +3
Stochastic simulation aims to compute output performance for complex models that lack analytical tractability. To ensure accurate prediction, the model needs to be calibrated and v…
Adaptive Importance Sampling for Efficient Stochastic Root Finding and Quantile Estimation
Shengyi He, Guangxin Jiang, Henry Lam +1
In solving simulation-based stochastic root-finding or optimization problems that involve rare events, such as in extreme quantile estimation, running crude Monte Carlo can be proh…
Model Calibration via Distributionally Robust Optimization: On the NASA Langley Uncertainty Quantification Challenge
Yuanlu Bai, Zhiyuan Huang, Henry Lam
We study a methodology to tackle the NASA Langley Uncertainty Quantification Challenge, a model calibration problem under both aleatory and epistemic uncertainties. Our methodology…