Hyperbolic grids and discrete random graphs
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We present an efficient algorithm for computing distances in hyperbolic grids. We apply this algorithm to work efficiently with a discrete variant of the hyperbolic random graph model. This model is gaining popularity in the analysis of scale-free networks, which are ubiquitous in many fields, from social network analysis to biology. We present experimental results conducted on real world networks.
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