Cover Image

Multilevel lattice-based kernel approximation for elliptic PDEs with random coefficients

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gilbert, Alexander D., Giles, Michael B., Kuo, Frances Y., Sloan, Ian H., Srikumar, Abirami
Format:	Preprint
Published:	2025
Subjects:	Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Density estimation for elliptic PDE with random input by preintegration and quasi-Monte Carlo methods
by: Gilbert, Alexander D., et al.
Published: (2024)

Bounding the spectral gap for an elliptic eigenvalue problem with uniformly bounded stochastic coefficients
by: Gilbert, Alexander D., et al.
Published: (2019)

Lattice-based Deep Neural Networks: Regularity and Tailored Regularization
by: Keller, Alexander, et al.
Published: (2026)

Minimal Subsampled Rank-1 Lattices for Multivariate Approximation with Optimal Convergence Rate
by: Bartel, Felix, et al.
Published: (2025)

Regularity and tailored regularization of Deep Neural Networks, with application to parametric PDEs in uncertainty quantification
by: Keller, Alexander, et al.
Published: (2025)

Deep learning methods for stochastic Galerkin approximations of elliptic random PDEs
by: Musco, Fabio, et al.
Published: (2024)

Finite element analysis of density estimation using preintegration for elliptic PDE with random input
by: Gilbert, Alexander D.
Published: (2025)

Lattice algorithms for multivariate approximation in periodic spaces with general weight parameters
by: Cools, Ronald, et al.
Published: (2019)

Multilevel quadrature formulae for the optimal control of random PDEs
by: Nobile, Fabio, et al.
Published: (2024)

Learning local Dirichlet-to-Neumann maps of nonlinear elliptic PDEs with rough coefficients
by: Boutilier, Miranda, et al.
Published: (2024)

Multilevel Picard approximations overcome the curse of dimensionality in the numerical approximation of general semilinear PDEs with gradient-dependent nonlinearities
by: Neufeld, Ariel, et al.
Published: (2023)

Numerical approximation of elliptic problems with log-normal random coefficients
by: Wan, Xiaoliang, et al.
Published: (2018)

Sparse-grid polynomial interpolation approximation and integration for parametric and stochastic elliptic PDEs with lognormal inputs
by: Dũng, Dinh
Published: (2019)

General superconvergence for kernel-based approximation
by: Karvonen, Toni, et al.
Published: (2025)

Preconditioners based on Voronoi quantizers of random variable coefficients for stochastic elliptic partial differential equations
by: Venkovic, Nicolas, et al.
Published: (2024)

Quasi-optimal nonconforming approximation of elliptic PDEs with contrasted coefficients and minimal regularity
by: Ern, Alexandre, et al.
Published: (2019)

Adaptive meshfree approximation for linear elliptic partial differential equations with PDE-greedy kernel methods
by: Wenzel, Tizian, et al.
Published: (2022)

$L_2$-approximation using randomized lattice algorithms
by: Cai, Mou, et al.
Published: (2024)

Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
by: Schütte, Janina Enrica, et al.
Published: (2024)

Convergence and error control of consistent PINNs for elliptic PDEs
by: Bonito, Andrea, et al.
Published: (2024)

Low-rank approximation of analytic kernels
by: Webb, Marcus
Published: (2025)

Smoothed Circulant Embedding with Applications to Multilevel Monte Carlo Methods for PDEs with Random Coefficients
by: Istratuca, Anastasia, et al.
Published: (2023)

$hp$-robust multigrid solver on locally refined meshes for FEM discretizations of symmetric elliptic PDEs
by: Innerberger, Michael, et al.
Published: (2022)

Multilevel Picard algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities
by: Neufeld, Ariel, et al.
Published: (2023)

Boundary corrections for kernel approximation to differential operators
by: Christlieb, Andrew, et al.
Published: (2024)

Multidimensional adaptive order GP-WENO via kernel-based reconstruction
by: May, Ian, et al.
Published: (2023)

Weak TransNet: A Petrov-Galerkin based neural network method for solving elliptic PDEs
by: Xu, Zhihang, et al.
Published: (2025)

An efficient solver based on low-rank approximation and Neumann matrix series for unsteady diffusion-type partial differential equations with random coefficients
by: Zhu, Yujun, et al.
Published: (2026)

Multilevel-Langevin pathwise average for Gibbs approximation
by: Egéa, Maxime, et al.
Published: (2021)

Superfast iterative refinement of low rank approximation of a matrix based on ALS method and random sampling
by: Luan, Qi, et al.
Published: (2019)

Quasi-Monte Carlo methods for uncertainty quantification of tumor growth modeled by a parametric semi-linear parabolic reaction-diffusion equation
by: Gilbert, Alexander D., et al.
Published: (2025)

A persistent-homology-based Bayesian prior for potential coefficient reconstruction in an elliptic PDE
by: Deng, Zhiliang, et al.
Published: (2025)

Optimal complexity of goal-oriented adaptive FEM for nonsymmetric linear elliptic PDEs
by: Bringmann, Philipp, et al.
Published: (2023)

Cost-optimal adaptive FEM with linearization and algebraic solver for semilinear elliptic PDEs
by: Brunner, Maximilian, et al.
Published: (2024)

Sharp inverse statements for kernel approximation: Superconvergence and saturation
by: Wenzel, Tizian
Published: (2026)

Conforming virtual element method for nondivergence form linear elliptic equations with Cordes coefficients
by: Bonnet, Guillaume, et al.
Published: (2024)

Accelerating the convergence of Newton's method for nonlinear elliptic PDEs using Fourier neural operators
by: Aghili, Joubine, et al.
Published: (2024)

Reproducing kernel methods for machine learning, PDEs, and statistics
by: LeFloch, Philippe G., et al.
Published: (2024)

Multilevel Monte Carlo methods for stochastic convection-diffusion eigenvalue problems
by: Cui, Tiangang, et al.
Published: (2023)

A Deep BSDE approximation of nonlinear integro-PDEs with unbounded nonlocal operators
by: Jakobsen, Espen Robstad, et al.
Published: (2024)