The ROMES method for statistical modeling of reduced-order-model error

  title={The ROMES method for statistical modeling of reduced-order-model error},
  author={Martin Drohmann and Kevin Carlberg},
This work presents a technique for statistically modeling errors introduced by reduced-order models. The method employs Gaussian-process regression to construct a mapping from a small number of computationally inexpensive ‘error indicators’ to a distribution over the true error. The variance of this distribution can be interpreted as the (epistemic) uncertainty introduced by the reduced-order model. To model normed errors, the method employs existing rigorous error bounds and residual norms as… CONTINUE READING
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