activity
20232026
most citedThe Fréchet derivative of the tensor t-function

3 citations · 4 across the 9 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

math.NA2023

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

Andreas Frommer, Michele Rinelli, Marcel Schweitzer

We consider the problem of estimating the trace of a matrix function . In certain situations, in particular if cannot be well approximated by a low-rank matrix, combin…

math.NA2023

Sketched and truncated polynomial Krylov methods: Evaluation of matrix functions

Davide Palitta, Marcel Schweitzer, Valeria Simoncini

Among randomized numerical linear algebra strategies, so-called sketching procedures are emerging as effective reduction means to accelerate the computation of Krylov subspace meth…

math.NA2023

Structured level-2 condition numbers of matrix functions

Bahar Arslan, Samuel D. Relton, Marcel Schweitzer

Matrix functions play an increasingly important role in many areas of scientific computing and engineering disciplines. In such real-world applications, algorithms working in float…

math.NA2023★ 1 cited

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

Marcel Schweitzer

When analyzing complex networks, an important task is the identification of those nodes which play a leading role for the overall communicability of the network. In the context of…

math.NA2023★ 3 cited

The Fréchet derivative of the tensor t-function

Kathryn Lund, Marcel Schweitzer

The tensor t-function, a formalism that generalizes the well-known concept of matrix functions to third-order tensors, is introduced in [K. Lund, The tensor t-function: a definitio…