An interactive toolbox for standardizing, validating, simulating, reducing, and exploring detailed biophysical models that can be used to reveal how morpho-electric properties map to dendritic and ...

We describe computationally efficient methods for Bayesian model selection. The methods select among mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs), ...

What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...

The Critical Path Method, known under its acronym CPM, is a way of optimizing the sequence of scheduled activities, or tasks, in a project. This is a management tool designed to ensure a project's ...

If you enjoyed this article, I’d like to ask for your support. Scientific American has served as an advocate for science and industry for 180 years, and right now may be the most critical moment in ...

Abstract: Learning-based distribution system state estimation (DSSE) methods typically depend on sufficient fully labeled data to construct mapping functions. However, collecting historical labels ...

ANY educational course in mechanics should undoubtedly be based first of all on experiment. If such is the case, it is practically impossible for any student using “graphical methods” to make the wild ...

ABSTRACT: Copulas are multivariate distribution functions with uniform marginal distributions. In this paper, we study a class of copulas called radial copulas, which is derived from residual ...

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Abstract: This paper proposes a graphical smooth switching control method for a four-switch Buck-Boost (FSBB) converter in fuel cell systems. Traditional FSBB converters can reduce average inductance ...