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Towards inferring network properties from epidemic data
However, the high-dimensionality of the exact models poses a challenge to both mathematical analysis and parameter inference.
Probabilistic predictions of SIS epidemics on networks based on population-level observations
To exploit this in a prediction framework, the exact high-dimensional stochastic model of an SIS epidemic on a network is approximated by a lower-dimensional surrogate model.
Inferring the time-varying functional connectivity of large-scale computer networks from emitted events
We consider the problem of inferring the functional connectivity of a large-scale computer network from sparse time series of events emitted by its nodes.
Using novelty-biased GA to sample diversity in graphs satisfying constraints
The structure of the network underlying many complex systems, whether artificial or natural, plays a significant role in how these systems operate.
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