output
19982026
most citedDeep Learning in Neural Networks: An Overview

18.2k citations

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34 papers · 1 filter

math.NA2024★ 1 cited

A Preconditioned Version of a Nested Primal-Dual Algorithm for Image Deblurring

Stefano Aleotti, Marco Donatelli, Rolf Krause +1

Variational models for image deblurring problems typically consist of a smooth term and a potentially non-smooth convex term. A common approach to solving these problems is using p…

math.NA2024

Two-level trust-region method with random subspaces

Andrea Angino, Alena Kopaničáková, Rolf Krause

We introduce a two-level trust-region method (TLTR) for solving unconstrained nonlinear optimization problems. Our method uses a composite iteration step, which is based on two dis…

math.NA2023★ 31 cited

Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies

Alena Kopaničáková, Hardik Kothari, George Em Karniadakis +1

We propose to enhance the training of physics-informed neural networks (PINNs). To this aim, we introduce nonlinear additive and multiplicative preconditioning strategies for the w…

math.NA2023★ 17 cited

Boundary Integral Formulation of the Cell-by-Cell Model of Cardiac Electrophysiology

Giacomo Rosilho de Souza, Rolf Krause, Simone Pezzuto

We propose a boundary element method for the accurate solution of the cell-by-cell bidomain model of electrophysiology. The cell-by-cell model, also called Extracellular-Membrane-I…

math.NA2022★ 1 cited

Nonlinear Schwarz preconditioning for Quasi-Newton methods

Hardik Kothari

We propose the nonlinear restricted additive Schwarz (RAS) preconditioning strategy to improve the convergence speed of limited memory quasi-Newton (QN) methods. We consider both "…

math.NA2022★ 15 cited

Level-based Blocking for Sparse Matrices: Sparse Matrix-Power-Vector Multiplication

Christie L. Alappat, Georg Hager, Olaf Schenk +1

The multiplication of a sparse matrix with a dense vector (SpMV) is a key component in many numerical schemes and its performance is known to be severely limited by main memory acc…

math.NA2022★ 24 cited

Nonlinear Field-split Preconditioners for Solving Monolithic Phase-field Models of Brittle Fracture

Alena Kopaničáková, Hardik Kothari, Rolf Krause

One of the state-of-the-art strategies for predicting crack propagation, nucleation, and interaction is the phase-field approach. Despite its reliability and robustness, the phase-…

math.NA2021★ 18 cited

Numerical solutions to linear transfer problems of polarized radiation II. Krylov methods and matrix-free implementation

Pietro Benedusi, Gioele Janett, Luca Belluzzi +1

Context. Numerical solutions to transfer problems of polarized radiation in solar and stellar atmospheres commonly rely on stationary iterative methods, which often perform poorly…

math.NA2021★ 19 cited

A Generalized Multigrid Method for Solving Contact Problems in Lagrange Multiplier based Unfitted Finite Element Method

Hardik Kothari, Rolf Krause

Internal interfaces in a domain could exist as a material defect or they can appear due to propagations of cracks. Discretization of such geometries and solution of the contact pro…

math.NA2021★ 8 cited

High-order interpolatory Serendipity Virtual Element Method for semilinear parabolic problems

Sergio Gómez

We propose an efficient method for the numerical approximation of a general class of two dimensional semilinear parabolic problems on polygonal meshes. The proposed approach takes…

math.NA2021★ 4 cited

A Multigrid Preconditioner for Jacobian-free Newton-Krylov Methods

Hardik Kothari, Alena Kopaničáková, Rolf Krause

In this work, we propose a multigrid preconditioner for Jacobian-free Newton-Krylov (JFNK) methods. Our multigrid method does not require knowledge of the Jacobian at any level of…

math.NA2021★ 3 cited

Multigrid and saddle-point preconditioners for unfitted finite element modelling of inclusions

Hardik Kothari, Rolf Krause

In this work, we consider the modeling of inclusions in the material using an unfitted finite element method. In the unfitted methods, structured background meshes are used and onl…

math.NA2020

A novel equi-dimensional finite element method for flow and transport in fractured porous media satisfying discrete maximum principle and conservation properties

Maria Giuseppina Chiara Nestola, Marco Favino

Numerical simulations of flow and transport in porous media usually rely on hybrid-dimensional models, i.e., the fracture is considered as objects of a lower dimension compared to…

math.NA2020★ 10 cited

A fast direct solver for nonlocal operators in wavelet coordinates

Helmut Harbrecht, Michael Multerer

In this article, we consider fast direct solvers for nonlocal operators. The pivotal idea is to combine a wavelet representation of the system matrix, yielding a quasi-sparse matri…

math.NA2020★ 126 cited

Verification benchmarks for single-phase flow in three-dimensional fractured porous media

Inga Berre, Wietse M. Boon, Bernd Flemisch +23

Flow in fractured porous media occurs in the earth's subsurface, in biological tissues, and in man-made materials. Fractures have a dominating influence on flow processes, and the…

math.NA2019★ 3 cited

High Performance Block Incomplete LU Factorization

Matthias Bollhöfer, Olaf Schenk, Fabio Verbosio

Many application problems that lead to solving linear systems make use of preconditioned Krylov subspace solvers to compute their solution. Among the most popular preconditioning a…

math.NA2019★ 53 cited

Recursive multilevel trust region method with application to fully monolithic phase-field models of brittle fracture

Alena Kopaničáková, Rolf Krause

The simulation of crack initiation and propagation in an elastic material is difficult, as crack paths with complex topologies have to be resolved. Phase-field approach allows to s…

math.NA2018★ 7 cited

Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit

Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai

Surface registration is one of the most fundamental problems in geometry processing. Many approaches have been developed to tackle this problem in cases where the surfaces are near…

math.NA2018★ 14 cited

High-dimensional and higher-order multifidelity Monte Carlo estimators

Alessio Quaglino, Simone Pezzuto, Rolf Krause

Multifidelity Monte Carlo methods rely on a hierarchy of possibly less accurate but statistically correlated simplified or reduced models, in order to accelerate the estimation of…

math.NA2018

Rapid computation of far-field statistics for random obstacle scattering

Helmut Harbrecht, Nikola Ilić, Michael D. Multerer

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the co…

math.NA2018★ 2 cited

A note on the domain mapping method with rough diffusion coefficients

M. D. Multerer

In this article, we consider elliptic diffusion problems on random domains with non-smooth diffusion coefficients. We start by illustrating the problems that arise from a non-smoot…

math.NA2016

An Iterative Approach for Time Integration Based on Discontinuous Galerkin Methods

Xiaozhou Li, Pietro Benedusi, Rolf Krause

We present a new class of iterative schemes for solving initial value problems (IVP) based on discontinuous Galerkin (DG) methods. Starting from the weak DG formulation of an IVP,…

math.NA2016★ 2 cited

Multiscale modeling, discretization, and algorithms: a survey in biomechanics

Marco Favino, Alessio Quaglino, Sonia Pozzi +2

Multiscale models allow for the treatment of complex phenomena involving different scales, such as remodeling and growth of tissues, muscular activation, and cardiac electrophysiol…

math.NA2014★ 29 cited

A high-order Boris integrator

Mathias Winkel, Robert Speck, Daniel Ruprecht

This work introduces the high-order Boris-SDC method for integrating the equations of motion for electrically charged particles in an electric and magnetic field. Boris-SDC relies…