34 citations to https://www.mathnet.ru/rus/mzm1360
  1. Diane Guignard, Peter Jantsch, “Nonlinear approximation of high-dimensional anisotropic analytic functions”, Journal of Approximation Theory, 300 (2024), 106040  crossref
  2. Anthony Nouy, Alexandre Pasco, “Dictionary-based model reduction for state estimation”, Adv Comput Math, 50:3 (2024)  crossref
  3. Francesco Romor, Giovanni Stabile, Gianluigi Rozza, “Non-linear Manifold Reduced-Order Models with Convolutional Autoencoders and Reduced Over-Collocation Method”, J Sci Comput, 94:3 (2023)  crossref
  4. Olga Mula, Lecture Notes in Mathematics, 2328, Model Order Reduction and Applications, 2023, 73  crossref
  5. Donsub Rim, Benjamin Peherstorfer, Kyle T. Mandli, “Manifold Approximations via Transported Subspaces: Model Reduction for Transport-Dominated Problems”, SIAM J. Sci. Comput., 45:1 (2023), A170  crossref
  6. Albert Cohen, Wolfgang Dahmen, Matthieu Dolbeault, Agustin Somacal, “Reduced order modeling for elliptic problems with high contrast diffusion coefficients”, ESAIM: M2AN, 57:5 (2023), 2775  crossref
  7. Daheng Cai, Chengbin Yao, Qifeng Liao, “A Stochastic Discrete Empirical Interpolation Approach for Parameterized Systems”, Symmetry, 14:3 (2022), 556  crossref
  8. Albert Cohen, Wolfgang Dahmen, Olga Mula, James Nichols, “Nonlinear Reduced Models for State and Parameter Estimation”, SIAM/ASA J. Uncertainty Quantification, 10:1 (2022), 227  crossref
  9. Balabanov O., Nouy A., “Randomized Linear Algebra For Model Reduction-Part II: Minimal Residual Methods and Dictionary-Based Approximation”, Adv. Comput. Math., 47:2 (2021), 26  crossref  isi
  10. Bonito A., Cohen A., DeVore R., Guignard D., Jantsch P., Petrova G., “Nonlinear Methods For Model Reduction”, ESAIM-Math. Model. Numer. Anal.-Model. Math. Anal. Numer., 55:2 (2021), 507–531  crossref  isi
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