Concepedia

SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes

Paul Saves, Rémi Lafage, Nathalie Bartoli, Youssef Diouane, Jasper Bussemaker, Thierry Lefèbvre, John T. Hwang, Joseph Morlier, Joaquim R. R. A. Martins

Advances in Engineering Software · 2023 · 117 citations · 56 references

Open access

Concepts

ComputingComputational EngineeringOptimizationStatistical ModelingStochastic ProcessesGaussian Process ModelingGaussian ProcessesHierarchical ModelingMultilevel ModelingSurrogate ModelingSurrogate-based OptimizationGaussian Process SurrogatesGaussian Random ProcessesHierarchical Surrogate ModelsHigh-dimensional Surrogate ModelingMultivariate Gaussian Processes

References

56

Scikit-learn: Machine Learning in Python

Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text

Computing, Computer Science, Artificial Intelligence +10

Efficient Global Optimization of Expensive Black-Box Functions

Donald R. Jones, Matthias Schonlau, William J. Welch · Journal of Global Optimization · 1998 · 7.8K citations

Natural Sciences, Computer Science, Algorithms +10

Bayesian Calibration of Computer Models

Marc C. Kennedy, Anthony O’Hagan · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2001 · 4.2K citations · Full text

Computing, Computer Science, Bayesian Data Analysis +11

A Taxonomy of Global Optimization Methods Based on Response Surfaces

Donald R. Jones · Journal of Global Optimization · 2001 · 2.1K citations

Architecture, Computational Engineering, Computer Science +14

An efficient algorithm for constructing optimal design of computer experiments

Ruichen Jin, Wei Chen, Agus Sudjianto · Journal of Statistical Planning and Inference · 2004 · 647 citations

Architecture, Computational Engineering, Design +14