Add to ORKGInspired by the novel ensemble method for the Navier-Stokes equations (NSE) in 2014 \cite{Nan-Layton-ensemble}, and the work of \cite{YanLuo-ZhuWang-ensemble}, this report develops an ensemble penalty method for the NSE. In addition, the method is extended to Monte Carlo random sampling. The combination allows greater ensemble sizes with reduced complexity and thus gives a longer predictability horizon
We discuss the analytic computation of autocorrelation functions for the generalized Hybrid Monte Ca...
We present a reduced basis Smagorinsky model. This model includes a non-linear eddy diffusion term t...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
We present a Multilevel Quasi-Monte Carlo algorithm for the solution of elliptic partial differentia...
AbstractIn this work we propose an iterative penalty method for addressing the Stokes equations. We ...
We present a Multi-Index Quasi-Monte Carlo method for the solution of elliptic partial differential ...
Mixed nite element approximation of reaction front propagation model in porous media is presented. T...
We employ linear wave theory to study long range attenuation of ocean waves caused by small, random ...
Exponential decay of correlation for the Stochastic Process associated to the Entropy Penalized Meth...
summary:In the paper the convergence of a mixed Runge--Kutta method of the first and second orders t...
International audienceAn increasing number of time-consuming simulators exhibit a complex noise stru...
In this short note we investigate the numerical performance of the method of artificial diffusion fo...
Through chaos decomposition we improve the Varadhan estimate for the rate of convergence of the cen...
A common idea in the PinT community is that Parareal, one of the most popular time-parallel algorith...
The efficient numerical simulation of models described by partial differential equations (PDEs) is a...
We discuss the analytic computation of autocorrelation functions for the generalized Hybrid Monte Ca...
We present a reduced basis Smagorinsky model. This model includes a non-linear eddy diffusion term t...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
We present a Multilevel Quasi-Monte Carlo algorithm for the solution of elliptic partial differentia...
AbstractIn this work we propose an iterative penalty method for addressing the Stokes equations. We ...
We present a Multi-Index Quasi-Monte Carlo method for the solution of elliptic partial differential ...
Mixed nite element approximation of reaction front propagation model in porous media is presented. T...
We employ linear wave theory to study long range attenuation of ocean waves caused by small, random ...
Exponential decay of correlation for the Stochastic Process associated to the Entropy Penalized Meth...
summary:In the paper the convergence of a mixed Runge--Kutta method of the first and second orders t...
International audienceAn increasing number of time-consuming simulators exhibit a complex noise stru...
In this short note we investigate the numerical performance of the method of artificial diffusion fo...
Through chaos decomposition we improve the Varadhan estimate for the rate of convergence of the cen...
A common idea in the PinT community is that Parareal, one of the most popular time-parallel algorith...
The efficient numerical simulation of models described by partial differential equations (PDEs) is a...
We discuss the analytic computation of autocorrelation functions for the generalized Hybrid Monte Ca...
We present a reduced basis Smagorinsky model. This model includes a non-linear eddy diffusion term t...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...