Author:
Billaud-Friess Marie,Macherey Arthur,Nouy Anthony,Prieur Clémentine
Publisher
Springer Science and Business Media LLC
Reference31 articles.
1. Nouy, A.: Low-rank tensor methods for model order reduction. SpringerLink, pp. 857–882 (2017). https://doi.org/10.1007/978-3-319-12385-1_21
2. Cohen, A., Dahmen, W., DeVore, R., Nichols, J.: Reduced basis greedy selection using random training sets. ESAIM: Math. Model. Numer. Anal. 54(5), 1509–1524 (2020)
3. Cai, D., Yao, C., Liao, Q.: A stochastic discrete empirical interpolation approach for parameterized systems. Symmetry 14(3), 556 (2022). https://doi.org/10.3390/sym14030556
4. Boyaval, S., Lelièvre, T.: A variance reduction method for parametrized stochastic differential equations using the reduced basis paradigm. Commun. Math. Sci. 8(3), 735–762 (2010). https://doi.org/10.4310/CMS.2010.v8.n3.a7
5. Blel, M.-R., Ehrlacher, V., Lelièvre, T.: Influence of sampling on the convergence rates of greedy algorithms for parameter-dependent random variables. (2021). arXiv:2105.14091