Olivier Zahm
Hivatkozott rá
Hivatkozott rá
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
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
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
On the representation and learning of monotone triangular transport maps
R Baptista, Y Marzouk, O Zahm
Foundations of Computational Mathematics, 1-46, 2023
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
Multifidelity dimension reduction via active subspaces
RR Lam, O Zahm, YM Marzouk, KE Willcox
SIAM Journal on Scientific Computing 42 (2), A929-A956, 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
Interpolation of inverse operators for preconditioning parameter-dependent equations
O Zahm, A Nouy
SIAM Journal on Scientific Computing 38 (2), A1044-A1074, 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
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
Data-free likelihood-informed dimension reduction of Bayesian inverse problems
T Cui, O Zahm
Inverse Problems 37 (4), 045009, 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
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
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
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
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
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
Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems
T Cui, XT Tong, O Zahm
Inverse Problems 38 (12), 124002, 2022
Self-reinforced polynomial approximation methods for concentrated probability densities
T Cui, S Dolgov, O Zahm
arXiv preprint arXiv:2303.02554, 2023
Minimizing rational functions: a hierarchy of approximations via pushforward measures
JB Lasserre, V Magron, S Marx, O Zahm
SIAM Journal on Optimization 31 (3), 2285-2306, 2021
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Cikkek 1–20