Estimating the state of epidemics spreading with graph neural networks

Abstract When an epidemic spreads into a population, it is often impractical or impossible to continuously monitor all subjects involved. As an alternative, we propose using algorithmic solutions that can infer the state of the whole population from a limited number of measures. We analyze the capab...

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Bibliographic Details
Main Authors: Tomy, Abhishek (Author), Razzanelli, Matteo (Author), Di Lauro, Francesco (Author), Rus, Daniela (Author), Della Santina, Cosimo (Author)
Format: Article
Language:English
Published: Springer Netherlands, 2022-07-11T14:22:37Z.
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