Artificial Intelligence.
Deep Learning.
Machine Learning.
Data-Driven Modeling.
Statistical Learning.
Model.
Physical Model.
Statistical Model.
Uncertainty Quantification. The quantification of the effect of various sources of error (from model, simulation, experiment) on a predicted quantity of interest.
Model Verification. The process of quantifying the accuracy of simulation codes used to implement mathematical models (i.e., are we solving the equations correctly?)
Model Validation. The process of determining the accuracy which mathematical models represent the physical processes of interest (i.e, are we solving the correct equations?)
Sensitivity Analysis. How uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model input.