# Improving Bayesian Network Structure Learning in the Presence of Measurement Error

19 Nov 2020

Structure learning algorithms that learn the graph of a Bayesian network from observational data often do so by assuming the data correctly reflect the true distribution of the variables. However, this assumption does not hold in the presence of measurement error, which can lead to spurious edges... (read more)

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