Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Perspectives on the integration between first-principles and data-driven modeling
Efficiently embedding and/or integrating mechanistic information with data-driven models is
essential if it is desired to simultaneously take advantage of both engineering principles and …
essential if it is desired to simultaneously take advantage of both engineering principles and …
Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures
Because humans are invariably exposed to complex chemical mixtures, estimating the
health effects of multi-pollutant exposures is of critical concern in environmental …
health effects of multi-pollutant exposures is of critical concern in environmental …
Computer model calibration using high-dimensional output
D Higdon, J Gattiker, B Williams… - Journal of the American …, 2008 - Taylor & Francis
This work focuses on combining observations from field experiments with detailed computer
simulations of a physical process to carry out statistical inference. Of particular interest here …
simulations of a physical process to carry out statistical inference. Of particular interest here …
A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization
Bayesian Optimization (BO), the application of Bayesian function approximation to finding
optima of expensive functions, has exploded in popularity in recent years. In particular, much …
optima of expensive functions, has exploded in popularity in recent years. In particular, much …
Choosing the sample size of a computer experiment: A practical guide
We provide reasons and evidence supporting the informal rule that the number of runs for an
effective initial computer experiment should be about 10 times the input dimension. Our …
effective initial computer experiment should be about 10 times the input dimension. Our …
[BOOK][B] Basics and trends in sensitivity analysis: Theory and practice in R
In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …
aerospace engineering, and nuclear safety, mathematical models turned into computer code …
Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models
The analysis of many physical and engineering problems involves running complex
computational models (simulation models, computer codes). With problems of this type, it is …
computational models (simulation models, computer codes). With problems of this type, it is …
Integrating dynamic Bayesian network and physics-based modeling for risk analysis of a time-dependent power distribution system during hurricanes
Hurricane is one of the major natural hazards that bring significant damages and failures to
the power distribution system for many coastal regions. For better decision-making, pre …
the power distribution system for many coastal regions. For better decision-making, pre …
Robust Gaussian stochastic process emulation
We consider estimation of the parameters of a Gaussian Stochastic Process (GaSP), in the
context of emulation (approximation) of computer models for which the outcomes are real …
context of emulation (approximation) of computer models for which the outcomes are real …