Date Recorded: Tuesday, November 17, 2020
Host: Erin DeCarlo
SwRI is pleased to present a webinar on Surrogate Models. This is the fourth webinar in a series on probabilistic methods for uncertainty quantification in engineering applications.
Surrogate models, also known as response surface models or emulators, constitute a powerful technique that enables a variety of analyses, including probabilistic assessments, which could otherwise be computationally prohibitive due to runtimes associated with detailed engineering models. This webinar will give an overview of the topic, including design of computer experiments, types of surrogate models, and goodness of fit assessment. Special focus will be given to the Gaussian Process surrogate modeling method, which is widely used due to its flexibility and accuracy, even in situations with very limited data.
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