68 citations · 89 across the 10 of their papers we have counts for
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Deflation-Based Spectral Preconditioning for the Conjugate Gradient Method on Perturbed Systems
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We consider sequences of large symmetric positive-definite linear systems in which spectral information from a reference matrix is reused to accelerate the solution of a nearby…
Accelerating an ensemble of variational data assimilations with randomized preconditioning
I. Daužickaitė, S. Gürol, M. Destouches +2
Ensembles of variational data assimilations (EDA) require solving systems of linear equations with iterative methods. The solution process can be accelerated using a limited memory…
A Spectral Preconditioner for the Conjugate Gradient Method with Iteration Budget
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We study the solution of large symmetric positive-definite linear systems in a matrix-free setting with a limited iteration budget. We focus on the preconditioned conjugate gradien…
An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
I. Daužickaitė, M. A. Freitag, S. Gürol +4
Variational data assimilation is a technique for combining measured data with dynamical models. It is a key component of Earth system state estimation and is commonly used in weath…
Block Alpha-Circulant Preconditioners for All-at-Once Diffusion-Based Covariance Operators
Jemima M. Tabeart, Selime Gürol, John W. Pearson +1
Covariance matrices are central to data assimilation and inverse methods derived from statistical estimation theory. Previous work has considered the application of an all-at-once…
An Efficient Scaled spectral preconditioner for sequences of symmetric positive definite linear systems
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We explore a scaled spectral preconditioner for the efficient solution of sequences of symmetric and positive-definite linear systems. We design the scaled preconditioner not only…
A filtered multilevel Monte Carlo method for estimating the expectation of cell-centered discretized random fields
Jérémy Briant, Paul Mycek, Mayeul Destouches +5
In this paper, we investigate the use of multilevel Monte Carlo (MLMC) methods for estimating the expectation of discretized random fields. Specifically, we consider a setting in w…
A general error analysis for randomized low-rank approximation methods
Youssef Diouane, Selime Gürol, Alexandre Scotto Di Perrotolo +1
We propose a general error analysis related to the low-rank approximation of a given real matrix in both the spectral and Frobenius norms. First, we derive deterministic error boun…
A note on preconditioning weighted linear least squares, with consequences for weakly-constrained variational data assimilation
Serge Gratton, Selime Gürol, Ehouarn Simon +1
The effect of preconditioning linear weighted least-squares using an approximation of the model matrix is analyzed, showing the interplay of the eigenstructures of both the model a…
On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation
S. Gratton, S. Gürol, E. Simon +1
This paper discusses the practical use of the saddle variational formulation for the weakly-constrained 4D-VAR method in data assimilation. It is shown that the method, in its orig…