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Multilevel Monte Carlo methods for random nonlinear eigenvalue problems
We develop a multilevel Monte Carlo (MLMC) estimator to compute statistical quantities of interest of solutions to parameter-dependent nonlinear eigenvalue problems. The main difficulty for this problem is that parametrized eigenpairs often lack a globally well-defined parameter-to-solution map due
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