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Found 2 papers, 1 papers with code
A Bayesian generative neural network framework for epidemic inference problems
The reconstruction of missing information in epidemic spreading on contact networks can be essential in the prevention and containment strategies.
Epidemic mitigation by statistical inference from contact tracing data
We conclude that probabilistic risk estimation is capable to enhance performance of digital contact tracing and should be considered in the currently developed mobile applications.
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