About: Deterministic scale-free network

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A scale-free network is a type of networks that is of particular interest of network science. It is characterized by its degree distribution following a power law. While the most widely known generative models for scale-free networks are stochastic, such as the Barabási–Albert model or the Fitness model can reproduce many properties of real-life networks by assuming preferential attachment and incremental growth, the understanding of deterministic scale-free networks leads to valuable, analytical results.

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  • A scale-free network is a type of networks that is of particular interest of network science. It is characterized by its degree distribution following a power law. While the most widely known generative models for scale-free networks are stochastic, such as the Barabási–Albert model or the Fitness model can reproduce many properties of real-life networks by assuming preferential attachment and incremental growth, the understanding of deterministic scale-free networks leads to valuable, analytical results. (en)
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  • A scale-free network is a type of networks that is of particular interest of network science. It is characterized by its degree distribution following a power law. While the most widely known generative models for scale-free networks are stochastic, such as the Barabási–Albert model or the Fitness model can reproduce many properties of real-life networks by assuming preferential attachment and incremental growth, the understanding of deterministic scale-free networks leads to valuable, analytical results. (en)
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  • Deterministic scale-free network (en)
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