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Markov process models for time-varying networks

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SNAW04 - Dynamic Networks

Many models for dynamic networks, such as the preferential attachment model, describe evolution by sequential addition of vertices and/or edges. Such models are not suited to networks whose connectivity varies over time, as in social relationships and other kinds of temporally varying interactions. For modeling in this latter setting, I develop the general theory of exchangeable Markov processes for time-varying networks and discuss relevant consequences.

This talk is part of the Isaac Newton Institute Seminar Series series.

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