7 citations · 11 across the 4 of their papers we have counts for
4 papers
TSEC: a framework for online experimentation under experimental constraints
Simon Mak, Yuanshuo Zhou, Lavonne Hoang +1
Thompson sampling is a popular algorithm for solving multi-armed bandit problems, and has been applied in a wide range of applications, from website design to portfolio optimizatio…
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations
Jialei Chen, Zhehui Chen, Chuck Zhang +1
Kriging (or Gaussian process regression) is a popular machine learning method for its flexibility and closed-form prediction expressions. However, one of the key challenges in appl…
BdryGP: a new Gaussian process model for incorporating boundary information
Liang Ding, Simon Mak, C. F. Jeff Wu
Gaussian processes (GPs) are widely used as surrogate models for emulating computer code, which simulate complex physical phenomena. In many problems, additional boundary informati…
Data-Driven Analysis and Common Proper Orthogonal Decomposition (CPOD)-Based Spatio-Temporal Emulator for Design Exploration
Shiang-Ting Yeh, Xingjian Wang, Chih-Li Sung +5
The present study proposes a data-driven framework trained with high-fidelity simulation results to facilitate decision making for combustor designs. At its core is a surrogate mod…