Fast sampling of parameterised Gaussian random fields
From MaRDI portal
Publication:1987947
DOI10.1016/j.cma.2019.02.003zbMath1441.65001arXiv1804.11157OpenAlexW2798302131MaRDI QIDQ1987947
Jonas Latz, Marvin Eisenberger, Elisabeth Ullmann
Publication date: 16 April 2020
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.11157
spatial statisticsuncertainty quantificationreduced basis methodsBayesian inverse problemKarhunen-Loève expansion
Random fields (60G60) Random fields; image analysis (62M40) Bayesian inference (62F15) Monte Carlo methods (65C05) Numerical methods for eigenvalue problems for boundary value problems involving PDEs (65N25) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21)
Related Items
Bayesian Inverse Problems Are Usually Well-Posed ⋮ Multilevel approximation of Gaussian random fields: Fast simulation ⋮ Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances ⋮ Regularity and convergence analysis in Sobolev and Hölder spaces for generalized Whittle-Matérn fields ⋮ Determination of the reaction coefficient in a time dependent nonlocal diffusion process ⋮ Stochastic field simulation of slope stability problems: improvement and reduction of computational effort ⋮ Bayesian inference of random fields represented with the Karhunen-Loève expansion ⋮ On the Well-posedness of Bayesian Inverse Problems ⋮ Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems
Uses Software
Cites Work
- Numerical methods for the discretization of random fields by means of the Karhunen-Loève expansion
- Multiscale model reduction method for Bayesian inverse problems of subsurface flow
- Hyperpriors for Matérn fields with applications in Bayesian inversion
- Application of hierarchical matrices for computing the Karhunen-Loève expansion
- An implicit restarted Lanczos method for large symmetric eigenvalue problems
- Fast random field generation with \(H\)-matrices
- Fast model updating coupling Bayesian inference and PGD model reduction
- Weak convergence of Galerkin approximations for fractional elliptic stochastic PDEs with spatial white noise
- Hierarchical Bayesian level set inversion
- Faster computation of the Karhunen-Loève expansion using its domain independence property
- Goal-oriented adaptive surrogate construction for stochastic inversion
- Simulation of multi-dimensional random fields by Karhunen-Loève expansion
- Karhunen-Loève approximation of random fields by generalized fast multipole methods
- Sparse-grid, reduced-basis Bayesian inversion
- Coordinate transformation and polynomial chaos for the Bayesian inference of a Gaussian process with parametrized prior covariance function
- Subspace Acceleration for Large-Scale Parameter-Dependent Hermitian Eigenproblems
- Optimal Model Management for Multifidelity Monte Carlo Estimation
- Strong and Weak Error Estimates for Elliptic Partial Differential Equations with Random Coefficients
- Inverse problems: A Bayesian perspective
- Handbook of Uncertainty Quantification
- Certified Reduced Basis Methods for Parametrized Partial Differential Equations
- The ROMES Method for Statistical Modeling of Reduced-Order-Model Error
- Reduced basis approximation anda posteriorierror estimates for parametrized elliptic eigenvalue problems
- Simultaneous reduced basis approximation of parameterized elliptic eigenvalue problems
- Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems
- Uncertainty Quantification and Weak Approximation of an Elliptic Inverse Problem
- Parallel Domain Decomposition Strategies for Stochastic Elliptic Equations. Part A: Local Karhunen--Loève Representations
- Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems
- Efficient approximation of random fields for numerical applications
- Fast and Exact Simulation of Stationary Gaussian Processes through Circulant Embedding of the Covariance Matrix
- An Algorithm for Simulating Stationary Gaussian Random Fields
- Output bounds for reduced-basis approximations of symmetric positive definite eigenvalue problems
- Templates for the Solution of Algebraic Eigenvalue Problems
- Analysis of Circulant Embedding Methods for Sampling Stationary Random Fields
- Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization
- Posterior consistency for Gaussian process approximations of Bayesian posterior distributions
- Fast Spatial Gaussian Process Maximum Likelihood Estimation via Skeletonization Factorizations
- Nonintrusive Uncertainty Analysis of Fluid-Structure Interaction with Spatially Adaptive Sparse Grids and Polynomial Chaos Expansion
- Sparse Approximations of Fractional Matérn Fields
- Reduced Basis Isogeometric Mortar Approximations for Eigenvalue Problems in Vibroacoustics
- Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes
- A Generalized Polynomial Chaos-Based Method for Efficient Bayesian Calibration of Uncertain Computational Models
- Stochastic Collocation for Elliptic PDEs with Random Data: The Lognormal Case
- The Bayesian Choice
- A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields
- Coarse-Grid Sampling Interpolatory Methods for Approximating Gaussian Random Fields
- Reduced Basis Methods for Partial Differential Equations
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
- Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen–Loève expansion
- Accurate Solution of Bayesian Inverse Uncertainty Quantification Problems Combining Reduced Basis Methods and Reduction Error Models
- Sequential Monte Carlo methods for Bayesian elliptic inverse problems
- MCMC methods for functions: modifying old algorithms to make them faster
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
