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Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
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Smolyak approximation

SIAM Review - A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

1 min read · Thu, May 6 2010

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uncertainty quantification Smolyak approximation

This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables.

Extensions of Dynamic Programming, Machine Learning, Discrete Optimization (TREES)

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