Network reconstruction from infection cascades
نویسندگان
چکیده
منابع مشابه
Network reconstruction from infection cascades
Reconstructing propagation networks from observations is a fundamental inverse problem, and it’s crucial to understand and control dynamics in complex systems. Here we show that it is possible to reconstruct the whole structure of an interaction network and to simultaneously infer the complete time course of activation spreading, relying just on single snapshots of a small number of activity ca...
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Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the...
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Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their compu...
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In many real-world scenarios, the underlying network over which the diffusions and propagations spread is unobserved, i.e. the edges of the network are invisible. In such cases, we can only infer the network structure from underlying observations. The goal of this paper is to find a model that generates realistic cascades with observed data, so that it can help us with link prediction and outli...
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ژورنال
عنوان ژورنال: Journal of The Royal Society Interface
سال: 2019
ISSN: 1742-5689,1742-5662
DOI: 10.1098/rsif.2018.0844