| Gradient-based dimension reduction of multivariate vector-valued functions O Zahm, PG Constantine, C Prieur, YM Marzouk SIAM Journal on Scientific Computing 42 (1), A534-A558, 2020 | 103 | 2020 |
| Certified dimension reduction in nonlinear Bayesian inverse problems O Zahm, T Cui, K Law, A Spantini, Y Marzouk Mathematics of Computation 91 (336), 1789-1835, 2022 | 89 | 2022 |
| Greedy inference with structure-exploiting lazy maps M Brennan, D Bigoni, O Zahm, A Spantini, Y Marzouk Advances in Neural Information Processing Systems 33, 8330-8342, 2020 | 59* | 2020 |
| Shared low-dimensional subspaces for propagating kinetic uncertainty to multiple outputs W Ji, J Wang, O Zahm, YM Marzouk, B Yang, Z Ren, CK Law Combustion and Flame 190, 146-157, 2018 | 58 | 2018 |
| On the representation and learning of monotone triangular transport maps R Baptista, Y Marzouk, O Zahm Foundations of Computational Mathematics, 1-46, 2023 | 56* | 2023 |
| Multifidelity dimension reduction via active subspaces RR Lam, O Zahm, YM Marzouk, KE Willcox SIAM Journal on Scientific Computing 42 (2), A929-A956, 2020 | 53 | 2020 |
| A tensor approximation method based on ideal minimal residual formulations for the solution of high-dimensional problems∗ M Billaud-Friess, A Nouy, O Zahm ESAIM: Mathematical Modelling and Numerical Analysis 48 (6), 1777-1806, 2014 | 48 | 2014 |
| Interpolation of inverse operators for preconditioning parameter-dependent equations O Zahm, A Nouy SIAM Journal on Scientific Computing 38 (2), A1044-A1074, 2016 | 42 | 2016 |
| Randomized residual-based error estimators for parametrized equations K Smetana, O Zahm, AT Patera SIAM journal on scientific computing 41 (2), A900-A926, 2019 | 28 | 2019 |
| Nonlinear dimension reduction for surrogate modeling using gradient information D Bigoni, Y Marzouk, C Prieur, O Zahm Information and Inference: A Journal of the IMA 11 (4), 1597-1639, 2022 | 26 | 2022 |
| Data-free likelihood-informed dimension reduction of Bayesian inverse problems T Cui, O Zahm Inverse Problems 37 (4), 045009, 2021 | 23 | 2021 |
| Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction T Cui, S Dolgov, O Zahm Journal of Computational Physics 485, 112103, 2023 | 20 | 2023 |
| Learning non-Gaussian graphical models via Hessian scores and triangular transport R Baptista, R Morrison, O Zahm, Y Marzouk Journal of Machine Learning Research 25 (85), 1-46, 2024 | 15 | 2024 |
| A fast boundary element method for the solution of periodic many-inclusion problems via hierarchical matrix techniques P Cazeaux, O Zahm ESAIM: Proceedings and Surveys 48, 156-168, 2015 | 14* | 2015 |
| Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective R Baptista, Y Marzouk, O Zahm arXiv preprint arXiv:2207.08670, 2022 | 13 | 2022 |
| Randomized residual‐based error estimators for the proper generalized decomposition approximation of parametrized problems K Smetana, O Zahm International Journal for Numerical Methods in Engineering 121 (23), 5153-5177, 2020 | 13 | 2020 |
| Projection-based model order reduction methods for the estimation of vector-valued variables of interest O Zahm, M Billaud-Friess, A Nouy SIAM Journal on Scientific Computing 39 (4), A1647-A1674, 2017 | 10 | 2017 |
| Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems T Cui, XT Tong, O Zahm Inverse Problems 38 (12), 124002, 2022 | 8 | 2022 |
| Principal feature detection via ϕ-Sobolev inequalities MTC Li, Y Marzouk, O Zahm Bernoulli 30 (4), 2979-3003, 2024 | 5 | 2024 |
| Self-reinforced polynomial approximation methods for concentrated probability densities T Cui, S Dolgov, O Zahm arXiv preprint arXiv:2303.02554, 2023 | 5 | 2023 |
Youssef MarzoukProfessor, Massachusetts Institute of TechnologyVerified email at mit.edu
