Abstract:Network inference is the reverse-engineering problem of infering graphs from data. With the always increasing availability of data, methods based on probability assumptions that infer multiple intertwined networks have been proposed in literature. These methods, while being extremely flexible, have the major drawback of presenting a high number of hyper-parameters that need to be tuned. The tuning of hyperparameters, in unsupervised settings, can be performed through criteria based on likelihood or stability. … Show more
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