233 citations · 234 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 233 cited
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
Venkat Nemani, Luca Biggio, Xun Huan +6
On top of machine learning models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enablin…
stat.ML2020★ 1 cited
srMO-BO-3GP: A sequential regularized multi-objective constrained Bayesian optimization for design applications
Anh Tran, Mike Eldred, Scott McCann +1
Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capabilit…
cs.CE2020
A stochastic reduced-order model for statistical microstructure descriptors evolution
Anh Tran, Jing Sun, Dehao Liu +2
Integrated Computational Materials Engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and signif…