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Consider a graph split into two graphs by a series of cuts, as in Figure 10.
We consider a general framework for uncovering these unknown graphs by a sequence of 'tests' or 'questions'questions
Results at p < 0.05 or p < 0.01 are denoted in graphs by a single or double asterisk, respectively.
Random graphs were generated from the experimentally obtained graphs by a constrained shuffle of the vertices keeping both the number of vertices and the degree of distribution.
Furthermore, the networks were also analyzed using another cluster algorithm for graphs called MCL (Markov Cluster algorithm, http://micans.org/mcl/) [20] that finds cluster structure in graphs by a mathematical bootstrapping procedure.
The trend lines, which are based on estimated mortality rates, are shown in the graphs by a dotted line.
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We refer to the signed DSR-graph as the graph identical to the DSR-graph given by (a - b), but with the la - b replaced buttheir signs.
We introduce a theory of bounded evaluability, to query big graphs by accessing a bounded amount of the data.
Consider deforming the path metric of a unimodular random graph by a (unimodular) reweighting of its vertices.
This paper considers the problem of augmenting a given graph by a cheapest possible set of additional edges in order to make the graph edge-biconnected.
We show how to twist the C⁎-algebra of a k-graph by a T-valued 2-cocycle and demonstrate that examples include all noncommutative tori.
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