When: February 15, 2017, 12:30 PM
Location: 3rd Floor Orchard View Room , Discovery Building
Contact: 608-316-4401, firstname.lastname@example.org
Optimal sampling in multifidelity Monte Carlo methods for uncertainty propagation
In uncertainty propagation, coefficients, boundary conditions, and other key inputs of computational models are given as random variables and one is interested in estimating statistical moments of the corresponding model outputs. Estimating the moments with crude Monte Carlo can become prohibitively expensive in cases where a single model solve is already computationally demanding. We present multifidelity methods that leverage low-cost, inaccurate surrogate models for speedup and occasionally make recourse to the expensive high-fidelity model to establish unbiased estimators, even in the absence of error control for the surrogate models. We demonstrate our multifidelity methods for uncertainty propagation and rare event simulation on various numerical examples.
SILO is a lecture series with speakers from the UW faculty, graduate students or invited researchers that discuss mathematical related topics. The seminars are organized by WID’s Optimization research group and sponsored by generous support of the Advance Technology Group of the 3M Company and the Analytics Group of Northwestern Mutual.
SILO’s purpose is to provide a forum that helps connect and recruit mathematically-minded graduate students. SILO is a lunch-and-listen format, where speakers present interesting math topics while the audience eats lunch.