Search results
Results: 46
Number of items: 46
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Jansson, F., Edeling, W., Attema, J., & Crommelin, D. (2021). Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model. Philosophical Transactions of the Royal Society A - Mathematical, Physical and Engineering Sciences, 379(2197), Article 20200073. https://doi.org/10.1098/rsta.2020.0073 -
Gugole, F., Coffeng, L. E., Edeling, W., Sanderse, B., de Vlas, S. J., & Crommelin, D. (2021). Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model. PLoS Computational Biology, 17(9), Article 1009355. https://doi.org/10.1371/journal.pcbi.1009355 -
Crommelin, D., & Edeling, W. (2021). Resampling with neural networks for stochastic parameterization in multiscale systems. Physica D, 422, Article 132894. https://doi.org/10.1016/j.physd.2021.132894 -
Razaaly, N., Crommelin, D., & Congedo, P. M. (2020). Efficient estimation of extreme quantiles using adaptive kriging and importance sampling. International Journal for Numerical Methods in Engineering, 121(9), 2086-2105. https://doi.org/10.1002/nme.6300
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Edeling, W., & Crommelin, D. (2020). Reducing data-driven dynamical subgrid scale models by physical constraints. Computers and Fluids, 201, Article 104470. https://doi.org/10.1016/j.compfluid.2020.104470
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van den Oord, G., Jansson, F., Pelupessy, I., Chertova, M., Grönqvist, J. H., Siebesma, P., & Crommelin, D. (2020). A Python interface to the Dutch Atmospheric Large-Eddy Simulation. SoftwareX, 12, Article 100608. https://doi.org/10.1016/j.softx.2020.100608 -
Crommelin, D. T., Edeling, W., & Jansson, F. (2020). Tackling the Multiscale Challenge of Climate Modelling. ERCIM News, 121, 15-17. https://ercim-news.ercim.eu/en121 -
Wright, D. W., Richardson, R. A., Edeling, W., Lakhlili, J., Sinclair, R. C., Jancauskas, V., Suleimenova, D., Bosak, B., Kulczewski, M., Piontek, T., Kopta, P., Chirca, I., Arabnejad, H., Luk, O. O., Hoenen, O., Węglarz, J., Crommelin, D., Groen, D., & Coveney, P. V. (2020). Building Confidence in Simulation: Applications of EasyVVUQ. Advanced Theory and Simulations, 3(8), Article 1900246. https://doi.org/10.1002/adts.201900246 -
Groen, D., Richardson, R. A., Wright, D. W., Jancauskas, V., Sinclair, R., Karlshoefer, P., Vassaux, M., Arabnejad, H., Piontek, T., Kopta, P., Bosak, B., Lakhlili, J., Hoenen, O., Suleimenova, D., Edeling, W., Crommelin, D., Nikishova, A., & Coveney, P. V. (2019). Introducing VECMAtk - Verification, Validation and Uncertainty Quantification for Multiscale and HPC Simulations. In J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, R. Lam, V. V. Krzhizhanovskaya, M. H. Lees, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2019 : 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings (Vol. IV, pp. 479-492). (Lecture Notes in Computer Science; Vol. 11539). Springer. https://doi.org/10.1007/978-3-030-22747-0_36
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Bisewski, K., Crommelin, D., & Mandjes, M. (2019). Rare event simulation for steady-state probabilities via recurrency cycles. Chaos, 29(3), Article 033131. https://doi.org/10.1063/1.5080296
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