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By Roger Ghanem, Olivier Le Mâitre, Olivier Le Mâitre and Chris Schwab


There has been a recent surge of interest within computational science and engineering, in the numerical resolution of physical problems described by probabilistic models. This generates a pressing need for the construction of probabilistic models that reflect, with controllable fidelity, the weight of evidence present in the experimental data. In these two talks I will describe the mathematical structure of this problem and its associated challenges. I will also describe recent efforts aimed at constructing models that simultaneously lend themselves to numerical resolution using function approximation techniques (a-la Polynomial Chaos), and to model validation

Year: 2011
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