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Kristian Debrabant
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2020 – today
- 2024
- [j8]Minoo Kamrani, Kristian Debrabant
, Nahid Jamshidi:
Exponential Euler method for stiff stochastic differential equations with additive fractional Brownian noise. Int. J. Comput. Math. 101(3): 357-371 (2024) - 2023
- [i6]Nahid Jamshidi, Minoo Kamrani, Kristian Debrabant:
Exponential Euler method for stiff stochastic differential equations with additive fractional Brownian noise. CoRR abs/2308.13224 (2023) - [i5]Alemayehu Adugna Arara, Kristian Debrabant, Anne Kværnø:
B-series for SDEs with application to exponential integrators for non-autonomous semi-linear problems. CoRR abs/2310.09179 (2023) - 2022
- [i4]Nicklas Sindlev Andersen, Marco Chiarandini, Kristian Debrabant:
Dynamic Origin-Destination Matrix Estimation in Urban Traffic Networks. CoRR abs/2202.00099 (2022) - 2020
- [i3]David Cohen, Kristian Debrabant, Andreas Rößler:
High order numerical integrators for single integrand SDEs. CoRR abs/2004.12887 (2020)
2010 – 2019
- 2019
- [j7]Kristian Debrabant
, Azadeh Ghasemifard
, Nicky C. Mattsson
:
Weak antithetic MLMC estimation of SDEs with the Milstein scheme for low-dimensional Wiener processes. Appl. Math. Lett. 91: 22-27 (2019) - [i2]Kristian Debrabant, Anne Kværnø, Nicky Cordua Mattsson:
Runge-Kutta Lawson schemes for stochastic differential equations. CoRR abs/1909.11629 (2019) - [i1]Kristian Debrabant, Anne Kværnø, Nicky Cordua Mattsson:
Lawson schemes for highly oscillatory stochastic differential equations and conservation of invariants. CoRR abs/1909.12287 (2019) - 2017
- [j6]Kristian Debrabant, Giovanni Samaey
, Przemyslaw Zielinski
:
A Micro-Macro Acceleration Method for the Monte Carlo Simulation of Stochastic Differential Equations. SIAM J. Numer. Anal. 55(6): 2745-2786 (2017) - 2016
- [c1]Troels Bo Jørgensen, Kristian Debrabant
, Norbert Krüger
:
Robust optimization of robotic pick and place operations for deformable objects through simulation. ICRA 2016: 3863-3870 - 2015
- [j5]Kristian Debrabant
, Severiano González-Pinto
, Domingo Hernández-Abreu:
On the global error of special Runge-Kutta methods applied to linear Differential Algebraic Equations. Appl. Math. Lett. 39: 53-59 (2015) - [j4]Kristian Debrabant, Andreas Rößler:
On the Acceleration of the Multi-Level Monte Carlo Method. J. Appl. Probab. 52(2): 307-322 (2015) - 2013
- [j3]Kristian Debrabant
, Espen R. Jakobsen
:
Semi-Lagrangian schemes for linear and fully non-linear diffusion equations. Math. Comput. 82(283): 1433-1462 (2013)
2000 – 2009
- 2008
- [j2]Kristian Debrabant
, Andreas Rößler
:
Classification of stochastic Runge-Kutta methods for the weak approximation of stochastic differential equations. Math. Comput. Simul. 77(4): 408-420 (2008) - [j1]Kristian Debrabant
, Anne Kværnø:
B-Series Analysis of Stochastic Runge-Kutta Methods That Use an Iterative Scheme to Compute Their Internal Stage Values. SIAM J. Numer. Anal. 47(1): 181-203 (2008)
Coauthor Index
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