where Cov (yi, yj) is the cross covariance between yi and yj, and σ yi denotes the standard deviation of yi. Unweighted graph edge can be derived from the functional connectivity by thresholding the ...

This is a survey paper on the second largest eigenvalue λ₂ of the adjacency matrix of a graph. Among the topics presented are the graphs with small λ₂, bounds for λ₂, algebraic connectivity, graphs ...

We present the zoomable adjacency matrix explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix graph representation ...

In this article, we employ a regression formulation to estimate the high-dimensional covariance matrix for a given network structure. Using prior information contained in the network relationships, we ...

Tables serve as essential structures for organizing and conveying structured information across a wide range of domains. Early methods for table structure recognition often model a table either as a ...