Gaussian graphical models have received considerable attention during the past four decades from the statistical and machine learning communities. In Bayesian treatments of this model, the G-Wishart ...

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that ...

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

Scagnostics is a Tukey neologism for the term scatterplot diagnostics. Scagnostics are characterizations of the 2D distributions of orthogonal pairwise projections of a set of points in ...

Students of statistics and researchers in search of a stats review will appreciate the Probability-Distributions app designed by Dr. Matthew Bognar at the University of Iowa. The app includes ...