Marcel Schweitzer | DeepAI

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∙ 08/15/2023

Analysis of stochastic probing methods for estimating the trace of functions of sparse symmetric matrices

We consider the problem of estimating the trace of a matrix function f(A...

0 Andreas Frommer, et al. ∙

∙ 06/10/2023

Sketched and truncated polynomial Krylov methods: Evaluation of matrix functions

Among randomized numerical linear algebra strategies, so-called sketchin...

0 Davide Palitta, et al. ∙

∙ 04/27/2023

Structured level-2 condition numbers of matrix functions

Matrix functions play an increasingly important role in many areas of sc...

0 Bahar Arslan, et al. ∙

∙ 03/02/2023

Sensitivity of matrix function based network communicability measures: Computational methods and a priori bounds

When analyzing complex networks, an important task is the identification...

0 Marcel Schweitzer, et al. ∙

∙ 02/19/2023

The Fréchet derivative of the tensor t-function

The tensor t-function, a formalism that generalizes the well-known conce...

0 Kathryn Lund, et al. ∙

∙ 08/24/2022

Randomized sketching for Krylov approximations of large-scale matrix functions

The computation of f(A)b, the action of a matrix function on a vector, i...

0 Stefan Güttel, et al. ∙

∙ 05/27/2022

Krylov subspace restarting for matrix Laplace transforms

A common way to approximate F(A)b – the action of a matrix function on a...

0 Andreas Frommer, et al. ∙

∙ 03/08/2022

Integral representations for higher-order Fréchet derivatives of matrix functions: Quadrature algorithms and new results on the level-2 condition number

We propose an integral representation for the higher-order Fréchet deriv...

0 Marcel Schweitzer, et al. ∙

∙ 11/11/2021

Decay bounds for Bernstein functions of Hermitian matrices with applications to the fractional graph Laplacian

For many functions of matrices f(A), it is known that their entries exhi...

0 Marcel Schweitzer, et al. ∙

∙ 09/03/2020

Analysis of probing techniques for sparse approximation and trace estimation of decaying matrix functions

The computation of matrix functions f(A), or related quantities like the...

0 Andreas Frommer, et al. ∙

∙ 08/29/2020

Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods

The Fréchet derivative L_f(A,E) of the matrix function f(A) plays an imp...

0 Peter Kandolf, et al. ∙

∙ 08/26/2020

Low-rank updates of matrix functions II: Rational Krylov methods

This work develops novel rational Krylov methods for updating a large-sc...

0 Bernhard Beckermann, et al. ∙

∙ 06/10/2020

A comparison of limited-memory Krylov methods for Stieltjes functions of Hermitian matrices

Given a limited amount of memory and a target accuracy, we propose and c...

0 Stefan Güttel, et al. ∙

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