Martin Eigel

SIAM J. Appl. Dyn. Syst., 2024

Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements.

[BibT_eX]

[DOI]

Janina E. Schütte

CoRR, 2024

A convergent adaptive finite element stochastic Galerkin method based on multilevel expansions of random fields.

[BibT_eX]

[DOI]

CoRR, 2024

Adaptive Multilevel Neural Networks for Parametric PDEs with Error Estimation.

[BibT_eX]

[DOI]

Janina E. Schütte

CoRR, 2024

Generative Modelling with Tensor Train approximations of Hamilton-Jacobi-Bellman equations.

[BibT_eX]

[DOI]

CoRR, 2024

Functional SDE approximation inspired by a deep operator network architecture.

[BibT_eX]

[DOI]

Charles Miranda

CoRR, 2024

2023

Pricing High-Dimensional Bermudan Options with Hierarchical Tensor Formats.

[BibT_eX]

[DOI]

SIAM J. Financial Math., June, 2023

Dynamical low-rank approximations of solutions to the Hamilton-Jacobi-Bellman equation.

[BibT_eX]

[DOI]

Reinhold Schneider

Numer. Linear Algebra Appl., May, 2023

Adaptive Nonintrusive Reconstruction of Solutions to High-Dimensional Parametric PDEs.

[BibT_eX]

[DOI]

Sebastian Heidenreich

SIAM J. Sci. Comput., April, 2023

Multilevel CNNs for Parametric PDEs.

[BibT_eX]

[DOI]

Cosmas Heiß

Ingo Gühring

J. Mach. Learn. Res., 2023

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures.

[BibT_eX]

[DOI]

CoRR, 2023

Weighted sparsity and sparse tensor networks for least squares approximation.

[BibT_eX]

[DOI]

Anthony Nouy

CoRR, 2023

Convergence of adaptive Galerkin FEM for parametric PDEs with lognormal coefficients.

[BibT_eX]

[DOI]

CoRR, 2023

2022

On the Convergence of Adaptive Stochastic Collocation for Elliptic Partial Differential Equations with Affine Diffusion.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., 2022

Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion.

[BibT_eX]

[DOI]

Manuel Marschall

Stat. Comput., 2022

Less interaction with forward models in Langevin dynamics.

[BibT_eX]

[DOI]

CoRR, 2022

Low-rank Wasserstein polynomial chaos expansions in the framework of optimal transport.

[BibT_eX]

[DOI]

CoRR, 2022

Topology Optimisation under Uncertainties with Neural Networks.

[BibT_eX]

[DOI]

Marvin Haase

Johannes Neumann

Algorithms, 2022

Tensor-Train Kernel Learning for Gaussian Processes.

[BibT_eX]

[DOI]

Max Kirstein

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2022

OptTopo: Automated set-point optimization for coupled systems using topology information.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Control, 2022

2021

Adaptive non-intrusive reconstruction of solutions to high-dimensional parametric PDEs.

[BibT_eX]

[DOI]

Sebastian Heidenreich

CoRR, 2021

Efficient approximation of high-dimensional exponentials by tensornetworks.

[BibT_eX]

[DOI]

Sebastian Heidenreich

CoRR, 2021

2020

Comparison of various uncertainty models with experimental investigations regarding the failure of plates with holes.

[BibT_eX]

[DOI]

Reliab. Eng. Syst. Saf., 2020

Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations.

[BibT_eX]

[DOI]

Numerische Mathematik, 2020

An Adaptive Stochastic Galerkin Tensor Train Discretization for Randomly Perturbed Domains.

[BibT_eX]

[DOI]

Manuel Marschall

Michael D. Multerer

SIAM/ASA J. Uncertain. Quantification, 2020

Convergence bounds for empirical nonlinear least-squares.

[BibT_eX]

[DOI]

Reinhold Schneider

CoRR, 2020

2019

Non-intrusive Tensor Reconstruction for High-Dimensional Random PDEs.

[BibT_eX]

[DOI]

Comput. Methods Appl. Math., 2019

Variational Monte Carlo - bridging concepts of machine learning and high-dimensional partial differential equations.

[BibT_eX]

[DOI]

Adv. Comput. Math., 2019

2018

Reproducing kernel Hilbert spaces and variable metric algorithms in PDE-constrained shape optimization.

[BibT_eX]

[DOI]

Kevin Sturm

Optim. Methods Softw., 2018

2017

SDE Based Regression for Linear Random PDEs.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2017

Adaptive stochastic Galerkin FEM with hierarchical tensor representations.

[BibT_eX]

[DOI]

Max Pfeffer

Reinhold Schneider

Numerische Mathematik, 2017

2016

An Adaptive Multilevel Monte Carlo Method with Stochastic Bounds for Quantities of Interest with Uncertain Data.

[BibT_eX]

[DOI]

Christian Merdon

Johannes Neumann

SIAM/ASA J. Uncertain. Quantification, 2016

Local Equilibration Error Estimators for Guaranteed Error Control in Adaptive Stochastic Higher-Order Galerkin Finite Element Methods.

[BibT_eX]

[DOI]

Christian Merdon

SIAM/ASA J. Uncertain. Quantification, 2016

Equilibration a Posteriori Error Estimation for Convection-Diffusion-Reaction Problems.

[BibT_eX]

[DOI]

Christian Merdon

J. Sci. Comput., 2016

Reliable Averaging for the Primal Variable in the Courant FEM and Hierarchical Error Estimators on Red-Refined Meshes.

[BibT_eX]

[DOI]

Carsten Carstensen

Comput. Methods Appl. Math., 2016

2015

Simulation of Composite Materials by a Network FEM with Error Control.

[BibT_eX]

[DOI]

Daniel Peterseim

Comput. Methods Appl. Math., 2015

2014

Functional A Posteriori Error Estimation for Stationary Reaction-Convection-Diffusion Problems.

[BibT_eX]

[DOI]