Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 46
Number of items: 46
  • Bisewski, K., Crommelin, D., & Mandjes, M. (2018). Simulation-based assessment of the stationary tail distribution of a stochastic differential equation. In M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, & B. Johansson (Eds.), WSC'18: proceedings of the 2018 Winter Simulation Conference, December 9-12, 2018, Gothenburg, Sweden : Simulation for a noble cause (pp. 1742-1753). (Proceedings of the Winter Simulation Conference; Vol. 2018). IEEE. https://doi.org/10.1109/WSC.2018.8632197
  • Open Access
    Bhaumik, D. (2018). Computational techniques for assessing power grids with wind energy and storage. [Thesis, externally prepared, Universiteit van Amsterdam].
  • Open Access
    Eggels, A. W., Crommelin, D. T., & Witteveen, J. A. S. (2018). Clustering-based collocation for uncertainty propagation with multivariate dependent inputs. International Journal for Uncertainty Quantification, 8(1), 43-59. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2018020215
  • Open Access
    Crommelin, D. (2018). Simulatie, chaos en onzekerheid. (Oratiereeks; No. 593). Universiteit van Amsterdam.
  • Open Access
    Crommelin, D. (2018). Cellular Automata for Clouds and Convection. In P.-Y. Louis, & F. R. Nardi (Eds.), Probabilistic Cellular Automata: Theory, Applications and Future Perspectives (pp. 327-339). (Emergence, Complexity and Computation; Vol. 27). Springer. https://doi.org/10.1007/978-3-319-65558-1_20
  • Berner, J., Achatz, U., Batté, L., Bengtsson, L., de la Cámara, A., Christensen, H. M., Colangeli, M., Coleman, D. R. B., Crommelin, D., Dolaptchiev, S. I., Franzke, C. L. E., Friederichs, P., Imkeller, P., Järvinen, H., Juricke, S., Kitsios, V., Lott, F., Lucarini, V., Mahajan, S., ... Yano, J.-I. (2017). Stochastic Parameterization: Toward a New View of Weather and Climate Models. Bulletin of the American Meteorological Society, 98(3), 565-587. https://doi.org/10.1175/BAMS-D-15-00268.1
  • Open Access
    Gottwald, G. A., Crommelin, D. T., & Franzke, C. L. E. (2017). Stochastic climate theory. In C. L. E. Franzke, & T. J. O'Kane (Eds.), Nonlinear and Stochastic Climate Dynamics (pp. 209-240). Cambridge University Press. https://arxiv.org/abs/1612.07474
  • Open Access
    Verheul, N., Viebahn, J., & Crommelin, D. (2017). Covariate-based stochastic parameterization of baroclinic ocean eddies. Mathematics of Climate and Weather Forecasting, 3(1), 90-117. https://doi.org/10.1515/mcwf-2017-0005
  • Bhaumik, D., Crommelin, D., & Zwart, B. (2016). A computational method for optimizing storage placement to maximize power network reliability. In T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, & S. E. Chick (Eds.), WSC'16 : Winter Simulation Conference: simulating complex service systems : Crystal Gateway Marriott, Arlington, VA, December 11-14, 2016 (pp. 883-894). IEEE. https://doi.org/10.1109/WSC.2016.7822150
  • Open Access
    Dorrestijn, J., Crommelin, D. T., Siebesma, A. P., Jonker, H. J. J., & Selten, F. (2016). Stochastic Convection Parameterization with Markov Chains in an Intermediate-Complexity GCM. Journal of the Atmospheric Sciences, 73(3), 1367-1382. https://doi.org/10.1175/JAS-D-15-0244.1
Page 4 of 5