Bayesian graphical models provide a principled framework for representing complex dependency structures among multivariate variables by combining graph theory with probabilistic inference. In these ...
Likelihood geometry examines the algebraic and geometric structure underlying maximum likelihood estimation on statistical models defined by polynomial equations. Central to this field is the maximum ...
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