36. R. D’Ambrosio, S. Di Donato, Discrete Gradient θ-Methods for Port-Hamiltonian Systems, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2025, Lecture Notes in Computer Science 15887, 225–236, Springer (2026). link
35. H. Biščević, R. D’Ambrosio, Mean-Square Monotonicity Analysis of θ-Maruyama Methods, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2025, Lecture Notes in Computer Science 15887, 237–248, Springer (2026). link
34. R. D’Ambrosio, S. Di Giovacchino, C. Scalone, Finding Sustainable Clusters in Supply Chains Dynamics via Graph Partitioning, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2025, Lecture Notes in Computer Science 15650, 366–374, Springer (2025). link
33. R. D’Ambrosio, S. Di Giovacchino, C. Scalone, Principles of stochastic geometric numerical integrations: dissipative problems and stochastic oscillators, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2021, AIP Conference Proceedings 2849, 020002 (2023). link
32. D. Conte, R. D’Ambrosio, G. Giordano, S. Mottola, B. Paternoster, Stiff problems nowadays: Novel numerics and fake news, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2021, AIP Conference Proceedings 2849, 020004 (2023). link
31. N. Carissimo, R. D’Ambrosio, M. Guzzo, S. Labarile, C. Scalone, Forecasting in Shipments: Comparison of Machine Learning Regression Algorithms on Industrial Applications for Supply Chain, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2023, Lecture Notes in Computer Science 13957, 462-470, Springer (2023). link
30. R. D’Ambrosio, P. Diaz de Alba, G. Giordano, B. Paternoster, A Modified SEIR Model: Stiffness Analysis and Application to the Diffusion of Fake News, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2022, Lecture Notes in Computer Science 13375, 90-104, Springer (2022). pdf
29. R. D’Ambrosio, S. Mottola, B. Paternoster, Stiffness Ratio and the Diffusion of Fake News, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2020, AIP Conference Proceedings 2425, 090004 (2022). link
28. D. Conte, R. D’Ambrosio, M.P. D’Arienzo, B. Paternoster, Semi-implicit Multivalue Almost Collocation Methods, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2020, AIP Conference Proceedings 2425, 090005 (2022). link
27. R. D’Ambrosio, G. Giordano, B. Paternoster, Numerical Conservation Issues for Stochastic Hamiltonian Problems, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2020, AIP Conference Proceedings 2425, 090007 (2022). link
26. D. Breda, J.K. Canci, R. D’Ambrosio, An Invitation to Stochastic Differential Equations in Healthcare, in J.K. Canci et al., Quantitative Models in Life Science Business - From Value Creation to Business Processes, SpringerBriefs in Economics, ISBN 978-3-031-11814-2, 97-110, Springer (2022). link
25. R. D'Ambrosio, S. Di Giovacchino, Optimal θ-Methods for Mean-Square Dissipative Stochastic Differential Equations, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2021, Lecture Notes in Computer Science 12949, 121-134 (2021). pdf
24. R. D'Ambrosio, C. Scalone, Asymptotic Quadrature Based Numerical Integration of Stochastic Damped Oscillators, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2021, Lecture Notes in Computer Science 12950, 622-629 (2021). pdf
23. D. Conte, R. D'Ambrosio, G. Giordano, B. Paternoster, Continuous Extension of Euler-Maruyama Method for Stochastic Differential Equations, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2021, Lecture Notes in Computer Science 12949, 135-145 (2021). pdf
22. G. Pagano, M.A. Budroni, R. D’ambrosio, D. Conte, A. Abou Hassan, S. Ristori, F. Rossi, B. Paternoster, A model for coupled Belousov-Zhabotinsky oscillators with delay, World Congress in Computational Mechanics and ECCOMAS Congress 2021, 700, 1-9 (2021). link
21. R. D'Ambrosio, S. Di Giovacchino, D. Pera, Parallel Numerical Solution of a 2DChemotaxis-Stokes System on GPUs Technology, in V.V. Krzhizhanovskaya et al. Computational Science – ICCS 2020, Lecture Notes in Computer Science 12137, 59-72 (2020). pdf
20. D. Conte, R. D'Ambrosio, G. Giordano, L. Gr. Ixaru, B. Paternoster, User-friendly expressions of the coefficients of some exponentially fitted methods, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2020, Lecture Notes in Computer Science 12249, 1-16 (2020). pdf
19. D. Conte, R. D'Ambrosio, M.P. D’Arienzo, B. Paternoster, Multivalue Almost Collocation Methods with Diagonal Coefficient Matrix, in O. Gervasi et al. Computational Science and Its Applications – ICCSA 2020, Lecture Notes in Computer Science 12249, 1-14 (2020). pdf
18. D. Conte, R. D'Ambrosio, M.P. D’Arienzo, B. Paternoster, Singly diagonally implicit multivalue collocation methods, in International Conference on Mathematics and Computers in Science and Engineering - MACISE2020, IEEE Catalog Number: CFP20S31-ART, ISBN: 978-1-7281-6695-7, 65-58 (2020). pdf
17. D. Conte, R. D'Ambrosio, G. Giordano, B. Paternoster, Regularized exponentially fitted methods for oscillatory problems, Journal of Physics: Conference Series 1564, 012013 (2020). pdf
16. D. Conte, R. D'Ambrosio, M.P. D’Arienzo, B. Paternoster, Highly stable multivalue collocation methods, Journal of Physics: Conference Series 1564, 012012 (2020). pdf
15. R. D'Ambrosio, M. Moccaldi, B. Paternoster, F. Rossi, Stochastic Numerical Models of Oscillatory Phenomena, in M. Pelillo et al. Artificial Life and Evolutionary Computation - WIVACE 2017, Communications in Computer and Information Science, doi: 10.1007/978-3-319-78658-2_5, Springer (2018). pdf
14. R. D'Ambrosio, M. Moccaldi, F. Rossi, B. Paternoster, On the employ of time series in the numerical treatment of differential equations modelling oscillatory phenomena, in F. Rossi et al. Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry - WIVACE 2016, Communications in Computer and Information Science, doi: 10.1007/978-3-319-57711-1_16, Springer (2017). pdf
13. A. Cardone, D. Conte, R. D'Ambrosio, B. Paternoster, On the numerical treatment of selected oscillatory evolutionary problems, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2016, AIP Conference Proceedings 1836(1), 160004 (2017). pdf
12. R. D'Ambrosio, Some recent advances in the numerical solution of differential equations, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2015, AIP Conference Proceedings 1738, 020002 (2016). pdf
11. R. D'Ambrosio, M. Moccaldi, B. Paternoster, Highly stable multivalue numerical methods, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2014, AIP Conference Proceedings 1648, 150005 (2015). pdf
10. R. D'Ambrosio, Multi-value numerical methods for Hamiltonian systems, in A. Abdulle et al., Numerical Mathematics and Advanced Applications - ENUMATH 2013, Lecture Notes in Computer Science and Engineering 103, 185-193, Springer (2015). pdf
9. R. D'Ambrosio, B. Paternoster, Diagonally implicit exponentially fitted Runge-Kutta methods with equation dependent coefficients. in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2012, AIP Conference Proceedings 1479, 1185-1188 (2012). pdf
8. D. Conte, R. D'Ambrosio, B. Paternoster, Advances on collocation based numerical methods for Ordinary Differential Equations and Volterra Integral Equations, in T. Simos, Recent Advances in Computational and Applied Mathematics, ISBN: 9789048199808, 41-46, Springer (2010). pdf
7. D. Conte, R. D'Ambrosio, M. Ferro, B. Paternoster, Piecewise-polynomial approximants for solutions of Functional Equations, in I. Capuzzo Dolcetta, M. Transirico, A. Vitolo, Percorsi Incrociati (in ricordo di Vittorio Cafagna), ISBN: 9788849828542, 101-113, Rubbettino Editore (2010). pdf
6. R. D'Ambrosio, G. Izzo, Z. Jackiewicz, Highly Stable General Linear Methods for Differential Systems, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2009, AIP Conference Proceedings 1168(1), 21-24 (2009). pdf
5. D. Conte, R. D'Ambrosio, M. Ferro, B. Paternoster, Practical construction of Two-Step Collocation Runge-Kutta methods for Ordinary Differential Equations, in E. Bernardis et al. Applied and Industrial Mathematics in Italy III, World Scientific Publishing, ISBN: 9789814280297, 78-288 (2009). pdf
4. R. D'Ambrosio, B. Paternoster, Runge-Kutta-Nystrom Stability for a Class of General Linear Methods for y''=f(x,y), in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2009, AIP Conference Proceedings 1168 (1), p. 444-447 (2009). pdf
3. D. Conte, R. D'Ambrosio, M. Ferro, B. Paternoster, Modified Collocation Techniques for Volterra Integral Equations, in E. Bernardis et al. Applied and Industrial Mathematics in Italy III, World Scientific Publishing, ISBN: 9789814280297, 268-277 (2009). pdf
2. R. D'Ambrosio, M. Ferro, B. Paternoster, Collocation-Based Two-Step Runge-Kutta Methods for Ordinary Differential Equations, in O. Gervasi et al. Computational Science and Its Applications - ICCSA 2008. Lecture Notes in Computer Science 5073, 736-751, Springer (2008). pdf
1. R. D'Ambrosio, M. Ferro, B. Paternoster, A general family of two step collocation methods for Ordinary Differential Equations, in T. E. Simos et al. Numerical Analysis and Applied Mathematics - ICNAAM 2007, AIP Conference Proceedings 936, 45-49 (2007). pdf