Abstract: Spectral graph theory is the study of the eigenvalues and eigenvectors of matrices associated with graphs. In this tutorial, we will try to provide some intuition as to why these ...

Guaranteed-Quality Anisotropic Mesh Generation. If you're in Soda Hall, you'll find copies of most of my papers hanging outside my office (625). Take the ones you want. FAR AND AWAY MY MOST POPULAR ...

This work aims to improve access to data on clustering within cancer cell populations. A cluster is defined as a small group of cells that maintain spatial proximity and exhibit coordinated behavior ...

Graphs are used as a model of complex relationships among data in biological science since the advent of systems biology in the early 2000. In particular, graph data analysis and graph data mining ...

Abstract: Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ...

Spectral graph clustering—clustering the vertices of a graph based on their spectral embedding—is of significant current interest, finding applications throughout the sciences. But as with clustering ...

Spectral algorithms are widely applied to data clustering problems, including finding communities or partitions in graphs and networks. We propose a way of encoding sparse data using a ...

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