58 citations · 87 across the 4 of their papers we have counts for
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math.NA2020
Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods
Peter Kandolf, Antti Koskela, Samuel D. Relton +1
The Fréchet derivative of the matrix function plays an important role in many different applications, including condition number estimation and network analysis.…
math.NA2016★ 9 cited
Computing the Action of Trigonometric and Hyperbolic Matrix Functions
Nicholas J. Higham, Peter Kandolf
We derive a new algorithm for computing the action of the cosine, sine, hyperbolic cosine, and hyperbolic sine of a matrix on a matrix , without first computing $f(A…
math.NA2015★ 58 cited
The Leja method revisited: backward error analysis for the matrix exponential
Marco Caliari, Peter Kandolf, Alexander Ostermann +1
The Leja method is a polynomial interpolation procedure that can be used to compute matrix functions. In particular, computing the action of the matrix exponential on a given vecto…