Search results
Results: 11
Number of items: 11
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Ye, D., Veen, L., Nikishova, A., Lakhlili, J., Edeling, W., Luk, O. O., Krzhizhanovskaya, V. V., & Hoekstra, A. G. (2021). Uncertainty quantification patterns for multiscale models. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379(2197), Article 20200072. https://doi.org/10.1098/rsta.2020.0072 -
Groen, D., Arabnejad, H., Jancauskas, V., Edeling, W. N., Jansson, F., Richardson, R. A., Lakhlili, J., Veen, L., Bosak, B., Kopta, P., Wright, D. W., Monnier, N., Karlshoefer, P., Suleimenova, D., Sinclair, R., Vassaux, M., Nikishova, A., Bieniek, M., Luk, O. O., ... Coveney, P. V. (2021). VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations. Philosophical Transactions of the Royal Society A - Mathematical, Physical and Engineering Sciences, 379(2197), Article 20200221. https://doi.org/10.1098/rsta.2020.0221 -
Ye, D., Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2021). Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model. Reliability Engineering and System Safety, 214, Article 107734. https://doi.org/10.1016/j.ress.2021.107734 -
de Vries, K., Nikishova, A., Czaja, B., Závodszky, G., & Hoekstra, A. G. (2020). Inverse Uncertainty Quantification of a cell model using a Gaussian Process metamodel. International Journal for Uncertainty Quantification, 10(4), 333-349. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2020033186 -
Nikishova, A., Comi, G. E., & Hoekstra, A. G. (2020). Sensitivity analysis based dimension reduction of multiscale models. Mathematics and Computers in Simulation, 170, 205-220. https://doi.org/10.1016/j.matcom.2019.10.013 -
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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Nikishova, A., & Hoekstra, A. G. (2019). Semi-intrusive uncertainty propagation for multiscale models. Journal of Computational Science, 35, 80-90. https://doi.org/10.1016/j.jocs.2019.06.007 -
Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2019). Semi-intrusive multiscale metamodelling uncertainty quantification with application to a model of in-stent restenosis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 377(2142), Article 2018154. https://doi.org/10.1098/rsta.2018.0154 -
Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2018). Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis. Cardiovascular Engineering and Technology, 9(4), 761-774. https://doi.org/10.1007/s13239-018-00372-4
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