Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies

DOI10.1137/18M1172259OpenAlexW2962962060MaRDI QIDQ4611541

Tim Dodwell, Gianluca Detommaso, Robert Scheichl

Publication date: 21 January 2019

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1802.07539

zbMATH Keywords

adaptivitymultilevel Monte Carlounbiased estimatorcomplexity theoremCLMCheterogeneous elliptic PDEs

Mathematics Subject Classification ID

Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Applications of statistics (62Pxx) Probabilistic methods, stochastic differential equations (65Cxx)

Related Items

A fully adaptive multilevel stochastic collocation strategy for solving elliptic PDEs with random data, Numerical analysis for time-dependent advection-diffusion problems with random discontinuous coefficients, Adaptive Multilevel Monte Carlo Methods for Stochastic Variational Inequalities, Context-Aware Surrogate Modeling for Balancing Approximation and Sampling Costs in Multifidelity Importance Sampling and Bayesian Inverse Problems, $hp$-Multilevel Monte Carlo Methods for Uncertainty Quantification of Compressible Navier--Stokes Equations, Recycling Samples in the Multigrid Multilevel (Quasi-)Monte Carlo Method, Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations, Multi-index ensemble Kalman filtering

Uses Software

• UMFPACK
• DUNE
• PDELab

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