A Bayesian MCMC sampler over graphs recovers network structure and edge probabilities from observed information cascades, outperforming a greedy baseline when data is scarce.
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Bayesian inference of network structure from information cascades
A Bayesian MCMC sampler over graphs recovers network structure and edge probabilities from observed information cascades, outperforming a greedy baseline when data is scarce.