NINNs: Nudging induced neural networks
Nudging induced neural networks (NINNs) algorithms are introduced to control and improve
the accuracy of deep neural networks (DNNs). The NINNs framework can be applied to …
the accuracy of deep neural networks (DNNs). The NINNs framework can be applied to …
Data assimilation in 2D incompressible Navier-Stokes equations, using a stabilized explicit leapfrog finite difference scheme run backward in time
AS Carasso - arXiv preprint arXiv:2411.14617, 2024 - arxiv.org
For the 2D incompressible Navier-Stokes equations, with given hypothetical non smooth
data at time $ T> 0$ that may not correspond to an actual solution at time $ T $, a previously …
data at time $ T> 0$ that may not correspond to an actual solution at time $ T $, a previously …
Data assimilation in 2D hyperbolic/parabolic systems using a stabilized explicit finite difference scheme run backward in time
AS Carasso - Applied Mathematics in Science and Engineering, 2024 - Taylor & Francis
An artificial example of a coupled system of three nonlinear partial differential equations
generalizing 2D thermoelastic vibrations, is used to demonstrate the effectiveness, as well …
generalizing 2D thermoelastic vibrations, is used to demonstrate the effectiveness, as well …
Increasing the Accuracy in Forecasting the Surface Drifter Trajectory by Using Data Assimilation
MR Abbasi - Pollution, 2023 - jpoll.ut.ac.ir
Predicting the path of pollution in the marine area is one of the most important concerns for
those involved in environmental studies. In this paper, we have discussed the capabilities of …
those involved in environmental studies. In this paper, we have discussed the capabilities of …
[PDF][PDF] Statement of Research
E Price - 2012 - stuff.mit.edu
2 Results Lower bounds. The main goal of sparse recovery is to minimize the number of
measurements. The seminal work of Candes, Romberg, and Tao [CRT06] presented a …
measurements. The seminal work of Candes, Romberg, and Tao [CRT06] presented a …