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Nucleoside binding by a surface lipoprotein governs conjugative ICE acquisition in mycoplasmas Open
Integrative and conjugative elements (ICEs) are major mediators of horizontal gene transfer in bacteria. However, the role of recipient cells in their acquisition has received little attention. Using the ruminant pathogens Mycoplasma agala…
Multilevel Monte Carlo methods for ensemble variational data assimilation Open
Ensemble variational data assimilation relies on ensembles of forecasts to estimate the background error covariance matrix B. The ensemble can be provided by an ensemble of data assimilations (EDA), which runs independent perturbed data as…
View article: WAVE CHARACTERISTICS FROM SPARSE DATA WITH IMPLICATIONS TO DERIVE COASTAL BATHYMETRY FROM REMOTE SENSING
WAVE CHARACTERISTICS FROM SPARSE DATA WITH IMPLICATIONS TO DERIVE COASTAL BATHYMETRY FROM REMOTE SENSING Open
Estimating bathymetry through remotely-sensed waves from optical imagery, lidar and radar, is a current major challenge of coastal science and engineering. Dense, abundant and regular dataset are generally required to capture wave characte…
Toward a New Parameterization of Fine-Scale Ocean-Atmosphere Interactions Based on a Machine Learning Approach Open
In the last decades, mesoscale air-sea interactions have received increasing interest from the scientific community. Mesoscale thermal (sea surface temperature influence, TFB) and mechanical (oceanic surface current influence, CFB) air-sea…
A FILTERED MULTILEVEL MONTE CARLO METHOD FOR ESTIMATING THE EXPECTATION OF CELL-CENTERED DISCRETIZED RANDOM FIELDS Open
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 which the input and output vectors of numerical simulators h…
Multilevel Monte Carlo methods for ensemble variational data assimilation Open
Ensemble variational data assimilation relies on ensembles of forecasts to estimate the background error covariance matrix B. The ensemble can be provided by an Ensemble of Data Assimilations (EDA), which runs independent perturbed data as…
Gaussian Anamorphosis for Ensemble Kalman Filter Analysis of SAR-Derived Wet Surface Ratio Observations Open
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A filtered multilevel Monte Carlo method for estimating the expectation of cell-centered discretized random fields Open
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 which the input and output vectors of numerical simulators h…
Dealing with Non-Gaussianity of SAR-Derived Wet Surface Ratio for Flood Extent Representation Improvement Open
Owing to advances in data assimilation, notably Ensemble Kalman Filter\n(EnKF), flood simulation and forecast capabilities have greatly improved in\nrecent years. The motivation of the research work is to reduce comprehensively\nthe uncert…
Gaussian Anamorphosis for Ensemble Kalman Filter Analysis of SAR-Derived Wet Surface Ratio Observations Open
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation (DA) strategies incorporating various types of observations; many are derived from spatial Earth Observation. This paper focuses on…
Neural prediction model for transition onset of a boundary layer in presence of two-dimensional surface defects Open
Predicting the laminar to turbulent transition is an important aspect of computational fluid dynamics because of its impact on skin friction. Traditional transition prediction methods such as local stability theory or the parabolized stabi…
Neural Prediction Model for Transition Onset of a Boundary-Layer in Presence of 2D Surface Defects (ODAS 2022) Open
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Multilevel Monte Carlo estimation of background error covariances in ensemble variational data assimilation Open
In ensemble variational (EnVar) data assimilation systems, background error covariances are sampled from an ensemble of forecasts evolving with time. One possible way of generating this ensemble is by running an Ensemble of Data Assimilati…
Neural Prediction Model for Transition Onset of a Boundary-Layer in Presence of 2D Surface Defects Open
International audience
p-norm regularization in variational data assimilation Open
We introduce a new formulation of the 4DVAR objective function by using as a penalty term a p-norm with 1 The performance of the proposed technique are assessed for different p-values by twin experiments on a linear advection equation. The…
An algorithm for the minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity Open
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most O(|log(ϵ)|ϵ−2) evaluations of…
Exploiting variable precision in GMRES Open
We describe how variable precision floating point arithmetic can be used in the iterative solver GMRES. We show how the precision of the inner products carried out in the algorithm can be reduced as the iterations proceed, without affectin…
Minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity Open
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most $O(|\log(ε)|\,ε^{-2})$ evalua…
Minimizing convex quadratic with variable precision Krylov methods Open
Iterative algorithms for the solution of convex quadratic optimization problems are investigated, which exploit inaccurate matrix-vector products. Theoretical bounds on the performance of a Conjugate Gradients and a Full-Orthormalization m…
Minimizing convex quadratic with variable precision conjugate gradients Open
We investigate the method of conjugate gradients, exploiting inaccurate matrix-vector products, for the solution of convex quadratic optimization problems. Theoretical performance bounds are derived, and the necessary quantities occurring …