Your English writing platform
Discover LudwigExact(9)
This class of algorithm utilizes "ant-like" agents which traverse the network and collectively construct routing policies.
This class of algorithm shows promise for solving some difficult highly-nonlinear problems where robustness and control of certain features, such as maintaining positive densities, is important.
However, this class of algorithm is primarily suited to photographs and other images with large colored regions with comparatively subtle color changes from one pixel to the next.
To the best knowledge of the authors, this is one of the proposed novelty for convergence of this class of algorithm with the spacer step ([26], p. 125).
In an agriculture example, this is a class of algorithm you might use to make sense of some of the images that are being taken from UAVs or satellites: What is the information in these images, what do they actually represent, and is there a certain pattern present in those images that would lend themselves to there being a particular pest or disease present?
We identify the 'correct' specification within each class of algorithm using standard diagnostic tests.
Similar(51)
We extend this class of algorithms in three ways.
Furthermore, we discuss important extensions within each class of algorithms.
We present a class of algorithms that guarantee validity in dynamic networks.
A class of algorithms for the numerical treatment of the Boltzmann equation is introduced.
The method works for a large class of algorithms that update its weights multiplicatively.
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