There is a complex relation between the mechanism of preferential attachment, scale-free degree distributions and hyperbolicity in complex networks. In fact, both preferential attachment and hidden hyperbolic spaces often generate scale-free networks. We show that there is actually a duality between a class of growing spatial networks based on preferential attachment on the sphere and a class of static random networks on the hyperbolic plane. Both classes of networks have the same scale-free degree distribution as the Barabasi-Albert model. As a limit of this correspondence, the Barabasi-Albert model is equivalent to a static random network on an hyperbolic space with infinite curvature
In this paper, we present a simple model of scale-free networks that incorporates both preferential ...
Through detailed analysis of scores of publicly available data sets corresponding to a wide range of...
We consider a model for complex networks that was introduced by Krioukov et al. (Phys Rev E 82 (2010...
There is a complex relation between the mechanism of preferential attachment, scale-free degree dist...
We obtain the degree distribution for a class of growing network models on flat and curved spaces. T...
Random graphs with power-law degrees can model scale-free networks as sparse topologies with strong ...
In this paper we study weighted distances in scale-free spatial network models: hyperbolic random gr...
The node degrees of large real-world networks often follow a power-law distribution. Such scale-free...
We show that heterogeneous degree distributions in observed scale-free topologies of complex network...
Two common features of many large real networks are that they are sparse and that they have strong c...
Abstract A remarkable approach for grasping the relevant statistical features of real networks with ...
Abstract. The combination of growth and preferential attachment is responsible for the power-law dis...
Network embedding is a frontier topic in current network science. The scale-free property of complex...
We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extend...
Many studies have considered the preferential attachment mechanism to cause scale-free networks. On ...
In this paper, we present a simple model of scale-free networks that incorporates both preferential ...
Through detailed analysis of scores of publicly available data sets corresponding to a wide range of...
We consider a model for complex networks that was introduced by Krioukov et al. (Phys Rev E 82 (2010...
There is a complex relation between the mechanism of preferential attachment, scale-free degree dist...
We obtain the degree distribution for a class of growing network models on flat and curved spaces. T...
Random graphs with power-law degrees can model scale-free networks as sparse topologies with strong ...
In this paper we study weighted distances in scale-free spatial network models: hyperbolic random gr...
The node degrees of large real-world networks often follow a power-law distribution. Such scale-free...
We show that heterogeneous degree distributions in observed scale-free topologies of complex network...
Two common features of many large real networks are that they are sparse and that they have strong c...
Abstract A remarkable approach for grasping the relevant statistical features of real networks with ...
Abstract. The combination of growth and preferential attachment is responsible for the power-law dis...
Network embedding is a frontier topic in current network science. The scale-free property of complex...
We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extend...
Many studies have considered the preferential attachment mechanism to cause scale-free networks. On ...
In this paper, we present a simple model of scale-free networks that incorporates both preferential ...
Through detailed analysis of scores of publicly available data sets corresponding to a wide range of...
We consider a model for complex networks that was introduced by Krioukov et al. (Phys Rev E 82 (2010...