Covariance Matrices and Influence Scores for Mean Field Variational Bayes

26 Feb 2015Ryan GiordanoTamara Broderick

Mean field variational Bayes (MFVB) is a popular posterior approximation method due to its fast runtime on large-scale data sets. However, it is well known that a major failing of MFVB is that it underestimates the uncertainty of model variables (sometimes severely) and provides no information about model variable covariance... (read more)

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