In this paper we study the manifold embedding of graphs resulting from the Young-Householder decomposition of the heat kernel [19].
Measuring Graph Similarity Using Spectral Geometry - ResearchGate
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Jun 25, 2016 · In this paper we study the manifold embedding of graphs resulting from the Young-Householder decomposition of the heat kernel [19].
To gauging the similarity of pairs of graphs, we require a means of comparing sets of such features without explicit correspondences between the nodes of the ...
Jan 31, 2018 · In this paper we develop a test for similarity between the inferred and the true network. Our research utilizes a network visualization tool.
Missing: Geometry. | Show results with:Geometry.
Apr 1, 2019 · We propose in this work to tackle the problem of graph classification using a spectral measurement of similarity called Joint Spectral ...
Missing: Geometry. | Show results with:Geometry.
Jul 23, 2019 · We propose in this work to tackle the problem of graph classification using a spectral measurement of similarity called Joint Spectral ...
In this work, we compare commonly used graph metrics and distance measures, and demonstrate their ability to discern between common topological features.
As similarity function on this data set we choose the Gaussian similarity function s(xi,xj) = exp(−|xi − xj|2/(2σ2)) with σ = 1. As similarity graph we consider ...
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In this paper, we describe the use of concepts from the areas of spectral-graph theory, kernel methods and differential geometry for the purposes of ...
ABSTRACT. The study of the topological structure of complex networks has fascinated researchers for several decades, and today.