Publications by Andreas Rößler

• Publications according to Zentralblatt MATH
• Publications according to Mathematical Reviews


• ORCID profile (link)
• ResearcherID profile (link)

Mathematical publications:


1. Claudine von Hallern, Ricarda Mißfeldt and Andreas Rößler: An exponential stochastic Runge-Kutta type method of order up to 1.5 for SPDEs of Nemytskii-type,
   IMA J. Numer. Anal., Vol. xx, No. x, xx-xx (2024). (link) (arXiv)
   
   
2. Felix Kastner and Andreas Rößler: An analysis of approximation algorithms for iterated stochastic integrals and a Julia and Matlab simulation toolbox,
   Numer. Algorithms, Vol. 93, No. 1, 27-66 (2023). (link) (arXiv)       (Julia Software LevyArea.jl) (Matlab Software LevyArea.m)
   
   
3. Claudine von Hallern and Andreas Rößler: A derivative-free Milstein type approximation method for SPDEs covering the non-commutative noise case,
   Stoch. PDE: Anal. Comp., Vol. 11, No. 4, 1672-1731 (2023). (link) (arXiv)
   
   
4. Jan Mrongowius and Andreas Rößler: On the approximation and simulation of iterated stochastic integrals and the corresponding Levy areas in terms of a multidimensional Brownian motion,
   Stoch. Anal. Appl., Vol. 40, No. 3, 397-425 (2022). (link) (arXiv)
   
   
5. David Cohen, Kristian Debrabant and Andreas Rößler: High order numerical integrators for single integrand Stratonovich SDEs,
   Appl. Numer. Math., Vol. 158, 264-270 (2020). (link) (arXiv)
   
   
6. Claudine von Hallern and Andreas Rößler: An Analysis of the Milstein Scheme for SPDEs without a Commutative Noise Condition,
   Monte Carlo and Quasi-Monte Carlo Methods 2018, pp. 503-521, Springer-Verlag (2020). (link) (arXiv)
   
   
7. Michael B. Giles, Kristian Debrabant and Andreas Rößler: Analysis of multilevel Monte Carlo path simulation using the Milstein discretisation,
   Discrete Contin. Dyn. Syst., Ser. B, Vol. 24, No. 8, 3881-3903 (2019). (link) (arXiv)
   
   
8. Claudine Leonhard and Andreas Rößler: Iterated stochastic integrals in infinite dimensions: approximation and error estimates,
   Stoch. PDE: Anal. Comp., Vol. 7, No. 2, 209-239 (2019). (link) (arXiv)
   
   
9. Amir Haghighi and Andreas Rößler: Split-step double balanced approximation methods for stiff stochastic differential equations,
   Int. J. Comput. Math., Vol. 96, No. 5, 1030-1047 (2019). (link)
   
   
10. Claudine Leonhard and Andreas Rößler: Enhancing the Order of the Milstein Scheme for Stochastic Partial Differential Equations with Commutative Noise,
    SIAM J. Numer. Anal., Vol. 56, No. 4, 2585-2622 (2018). (link) (arXiv)
    
    
11. Amir Haghighi, Seyed Mohammad Hosseini and Andreas Rößler: Diagonally drift-implicit Runge-Kutta methods of strong order one for stiff stochastic differential systems,
    J. Comp. Appl. Math., Vol. 293, 82-93 (2016). (link)
    
    
12. Kristian Debrabant and Andreas Rößler: On the acceleration of the multi-level Monte Carlo method,
    J. Appl. Probab., Vol. 52, No. 2, 307-322 (2015). (link) (arXiv)
    
    
13. Dominique Küpper, Anne Kværnø and Andreas Rößler: Stability analysis and classification of Runge-Kutta methods for index 1 stochastic differential-algebraic equations with scalar noise,
    Appl. Numer. Math., Vol. 96, 24-44 (2015). (link) (arXiv)
    
    
14. Kristian Debrabant and Andreas Rößler: Derivative-free weak approximation methods for stochastic differential equations in finance,
    Recent Developments in Computational Finance - Foundations, algorithms and applications, Vol. 14, Interdisciplinary Mathematical Sciences, pp. 299-315, World Scientific (2013). (link)
    
    
15. Dominique Küpper, Anne Kværnø and Andreas Rößler: A Runge-Kutta method for index 1 stochastic differential-algebraic equations with scalar noise,
    BIT Numerical Mathematics, Vol. 52, No. 2, 437-455 (2012). (link)
    
    
16. Andreas Rößler: Runge-Kutta methods for the strong approximation of solutions of stochastic differential equations,
    SIAM J. Numer. Anal., Vol. 48, No. 3, 922-952 (2010). (link)
    
    
17. Evelyn Buckwar, Andreas Rößler and Renate Winkler: Stochastic Runge-Kutta methods for Ito-SODEs with small noise,
    SIAM J. Sci. Comput., Vol. 32, No. 4, 1789-1808 (2010). (link)
    
    
18. Andreas Rößler: Strong and weak approximation methods for stochastic differential equations-some recent developments,
    Recent Developments in Applied Probability and Statistics, p. 127-153, Physica-Verlag/Springer (2010). (link) (Preprint)
    
    
19. Andreas Rößler: Stochastic Taylor expansions for functionals of diffusion processes,
    Stoch. Anal. Appl., Vol. 28, No. 3, 415-429 (2010). (link) (arXiv)
    
    
20. Andreas Rößler, Mohammed Seaïd and Mostafa Zahri: Numerical simulation of stochastic replicator models in catalyzed RNA-like polymers,
    Math. Comput. Simulation, Vol. 79, No. 12, 3577-3586 (2009). (link)
    
    
21. Andreas Rößler: Second order Runge-Kutta methods for Itô stochastic differential equations,
    SIAM J. Numer. Anal., Vol. 47, No. 3, 1713-1738 (2009). (link)
    
    
22. Kristian Debrabant and Andreas Rößler: Diagonally drift-implicit Runge-Kutta methods of weak order one and two for Itô SDEs and stability analysis,
    Appl. Numer. Math., Vol. 59, No. 3-4, 595-607 (2009). (link)
    
    
23. A. Neuenkirch, I. Nourdin, A. Rößler and S. Tindel: Trees and asymptotic expansions for fractional stochastic differential equations,
    Ann. Inst. Henri Poincaré Probab. Stat., Vol. 45, No. 1, 157-174 (2009). (link)
    
    
24. Kristian Debrabant and Andreas Rößler: Families of efficient second order Runge-Kutta methods for the weak approximation of Itô stochastic differential equations,
    Appl. Numer. Math., Vol. 59, No. 3-4, 582-594 (2009). (link)
    
    
25. Andreas Rößler, Mohammed Seaïd and Mostafa Zahri: Method of lines for stochastic boundary-value problems with additive noise,
    Appl. Math. Comput., Vol. 199, No. 1, 301-314 (2008). (link)
    
    
26. Kristian Debrabant and Andreas Rößler: Continuous Runge-Kutta methods for Stratonovich stochastic differential equations,
    Monte Carlo and Quasi-Monte Carlo Methods 2006, pp. 237-250, Springer-Verlag (2008). (link)
    
    
27. Kristian Debrabant and Andreas Rößler: Classification of stochastic Runge-Kutta methods for the weak approximation of stochastic differential equations,
    Math. Comput. Simulation, Vol. 77, No. 4, 408-420 (2008). (link)
    
    
28. Kristian Debrabant and Andreas Rößler: Continuous weak approximation for stochastic differential equations,
    J. Comput. Appl. Math., Vol. 214, No. 1, 259-273 (2008). (link)
    
    
29. Andreas Rößler: Second order Runge-Kutta methods for Stratonovich stochastic differential equations,
    BIT Numerical Mathematics, Vol. 47, No. 3, 657-680 (2007). (link)
    
    
30. Dominique Küpper, Jürgen Lehn and Andreas Rößler: A step size control algorithm for the weak approximation of stochastic differential equations,
    Numer. Algorithms, Vol. 44, No. 4, 335-346 (2007). (link)
    
    
31. Peter E. Kloeden and Andreas Rößler: Runge-Kutta methods for affinely controlled nonlinear systems,
    J. Comput. Appl. Math., 205 (2), 957-968 (2007). (link)
    
    
32. Andreas Rößler: Runge-Kutta methods for Itô stochastic differential equations with scalar noise,
    BIT Numerical Mathematics, Vol. 46, No. 1, 97-110 (2006). (link)
    
    
33. Andreas Rößler: Rooted tree analysis for order conditions of stochastic Runge-Kutta methods for the weak approximation of stochastic differential equations,
    Stochastic Anal. Appl., Vol. 24, No. 1, 97-134 (2006). (link) (arXiv)
    
    
34. Andreas Rößler: Explicit order 1.5 schemes for the strong approximation of Itô stochastic differential equations,
    Proc. Appl. Math. Mech., 5 (1), 817-818 (2005). (link)
    
    
35. Andreas Rößler: Stochastic Taylor expansions for the expectation of functionals of diffusion processes,
    Stochastic Anal. Appl., Vol. 22, No. 6, 1553-1576 (2004). (link) (arXiv)
    
    
36. Andreas Rößler: An adaptive discretization algorithm for the weak approximation of stochastic differential equations,
    Proc. Appl. Math. Mech., 4 (1), 19-22 (2004). (link)
    
    
37. Andreas Rößler: Runge-Kutta methods for Stratonovich stochastic differential equation systems with commutative noise,
    J. Comput. Appl. Math., 164-165, 613-627 (2004). (link)
    
    
38. Andreas Rößler: Coefficients of Runge-Kutta schemes for Itô stochastic differential equations,
    Proc. Appl. Math. Mech., 3 (1), 571-572 (2003). (link)
    
    
39. Andreas Rößler: Embedded stochastic Runge-Kutta methods,
    Proc. Appl. Math. Mech., 2 (1), 461-462 (2003). (link)
    
    
40. E. Kropat, A. Rössler, St. W. Pickl, G.-W. Weber: On theoretical and practical relations between discrete optimization and nonlinear optimization,
    Computational Technologies (Vychisl. Tekhnol.), 7, Spec. Iss., 27-62 (2002). (link)
    
    
41. J. Lehn, A. Rößler and O. Schein: Adaptive schemes for the numerical solution of SDEs - a comparison,
    J. Comput. Appl. Math., 138 (2), 297-308 (2002). (link)
    
    
42. E. Kropat, St. Pickl, A. Rössler, G.-W. Weber: A new algorithm from semi-infinite optimization for a problem of time-minimum control,
    Computational Technologies (Vychisl. Tekhnol.), 5, No.4, 67-81 (2000). (link)
    
    
    
    Further publications:
    
    
43. Britta Kubera, Claudine Leonhard, Andreas Rößler and Achim Peters: Stress-Related Changes in Body Form: Results from the Whitehall II Study,
    Obesity, Vol. 25, No. 9, 1625–1632 (2017). (link)