
Error estimates for fully discrete generalized FEMs with locally optimal spectral approximations
This paper is concerned with the error estimates of the fully discrete g...
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Multilevel Spectral Domain Decomposition
Highly heterogeneous, anisotropic coefficients, e.g. in the simulation o...
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GenEO coarse spaces for heterogeneous indefinite elliptic problems
Motivated by recent work on coarse spaces for Helmholtz problems, we pro...
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Novel design and analysis of generalized FE methods based on locally optimal spectral approximations
In this paper, the generalized finite element method (GFEM) for solving ...
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Multilevel quasiMonte Carlo for random elliptic eigenvalue problems II: Efficient algorithms and numerical results
Stochastic PDE eigenvalue problems often arise in the field of uncertain...
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Multilevel Delayed Acceptance MCMC with an Adaptive Error Model in PyMC3
Uncertainty Quantification through Markov Chain Monte Carlo (MCMC) can b...
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Multilevel quasiMonte Carlo for random elliptic eigenvalue problems I: Regularity and error analysis
Random eigenvalue problems are useful models for quantifying the uncerta...
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Multilevel Monte Carlo for quantum mechanics on a lattice
Monte Carlo simulations of quantum field theories on a lattice become in...
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Rank Bounds for Approximating Gaussian Densities in the TensorTrain Format
Low rank tensor approximations have been employed successfully, for exam...
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Multilevel DimensionIndependent LikelihoodInformed MCMC for LargeScale Inverse Problems
We present a nontrivial integration of dimensionindependent likelihood...
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A HighPerformance Implementation of a Robust Preconditioner for Heterogeneous Problems
We present an efficient implementation of the highly robust and scalable...
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Unified Analysis of PeriodizationBased Sampling Methods for Matérn Covariances
The periodization of a stationary Gaussian random field on a sufficientl...
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HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference
In this paper, we introduce Hierarchical Invertible Neural Transport (HI...
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Approximation and sampling of multivariate probability distributions in the tensor train decomposition
General multivariate distributions are notoriously expensive to sample f...
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A Stein variational Newton method
Stein variational gradient descent (SVGD) was recently proposed as a gen...
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Scheduling massively parallel multigrid for multilevel Monte Carlo methods
The computational complexity of naive, samplingbased uncertainty quanti...
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Robert Scheichl
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