most citedBeyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting

11 citations · 11 across the 1 of their papers we have counts for

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cs.LG2017★ 11 cited

Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting

Rebecca E. Morrison, Ricardo Baptista, Youssef Marzouk

We present an algorithm to identify sparse dependence structure in continuous and non-Gaussian probability distributions, given a corresponding set of data. The conditional indepen…