Texas A&M University 3 credits CVEN
Introduction to the use of Bayesian inference methods to solve mechanical inverse problems with varying evidence conditions; experimental observations, model complexity and expert beliefs; representation of the probabilistic calibration of models with varying parameters in space and time, in the form of boundary conditions, material properties, and even numerical parameters; improves the scientific and engineering inferences stemmed from research practice.
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