| The Leja method revisited: backward error analysis for the matrix exponential M Caliari, P Kandolf, A Ostermann, S Rainer SIAM Journal on Scientific Computing 38 (3), A1639-A1661, 2016 | 74 | 2016 |
| Comparison of software for computing the action of the matrix exponential M Caliari, P Kandolf, A Ostermann, S Rainer BIT Numerical Mathematics 54, 113-128, 2014 | 70 | 2014 |
| Magnus integrators on multicore CPUs and GPUs N Auer, L Einkemmer, P Kandolf, A Ostermann Computer Physics Communications 228, 115-122, 2018 | 27 | 2018 |
| Computing low‐rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods P Kandolf, A Koskela, SD Relton, M Schweitzer Numerical Linear Algebra with Applications 28 (6), e2401, 2021 | 20 | 2021 |
| Computing the action of trigonometric and hyperbolic matrix functions NJ Higham, P Kandolf SIAM Journal on Scientific Computing 39 (2), A613-A627, 2017 | 17 | 2017 |
| Backward error analysis of polynomial approximations for computing the action of the matrix exponential M Caliari, P Kandolf, F Zivcovich BIT Numerical Mathematics 58, 907-935, 2018 | 12 | 2018 |
| A block Krylov method to compute the action of the Fréchet derivative of a matrix function on a vector with applications to condition number estimation P Kandolf, SD Relton SIAM Journal on Scientific Computing 39 (4), A1416-A1434, 2017 | 10 | 2017 |
| A residual based error estimate for Leja interpolation of matrix functions P Kandolf, A Ostermann, S Rainer Linear Algebra and its Applications 456, 157-173, 2014 | 6 | 2014 |
| Computationally efficient exponential integrators P Kandolf Department of Mathematics, University of Innsbruck, 2016 | 3 | 2016 |
| Exponential integrators P Kandolf McMaster University, 2011 | 3 | 2011 |
| Innovative integrators for time dependent PDEs P Kandolf na, 2011 | 1 | 2011 |
| Image processing using Wavelets and Tight Frames P Kandolf | | 2009 |
| The Leja method in Python P Kandolf, A Ostermann | | |
| The backward error of the Leja method P Kandolf | | |
