Your English writing platform
Discover LudwigExact(60)
Levenberg-Marquardt minimization with Bayesian regularization is also implemented, providing an optimal regularized solution and insight into parametrization efficiency.
This regularization is performed before any discretization.
The problem of extra diffusion caused by regularization is discussed.
NOTE: unlike other minimizers, regularization is done in the minimizer, not the objective function.
Then a statement on how to perform the nonlinear regularization is presented specifically.
Bayesian regularization is applied to our network training scheme to improve the generalization capability.
The numerical solution of dynamic elastoplasticity problems using Tikhonov regularization is presented in this paper.
A robust descent type algorithm through adaptive regularization is designed to solve a geophysical inverse problem.
Therefore, a nuclear norm regularization is enforced to capture that sparse prior.
Tikhonov regularization is then applied to the obtained discrete ill-posed problem.
The general method of iterative regularization is concerned with application to the estimation of materials properties.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com