24 citations · 33 across the 5 of their papers we have counts for
4 papers · 1 filter
Complete collineations for maximum likelihood estimation
Gergely Bérczi, Eloise Hamilton, Philipp Reichenbach +1
We import the algebro-geometric notion of a complete collineation into the study of maximum likelihood estimation in directed Gaussian graphical models. A complete collineation pro…
Symmetries in Directed Gaussian Graphical Models
Visu Makam, Philipp Reichenbach, Anna Seigal
We define Gaussian graphical models on directed acyclic graphs with coloured vertices and edges, calling them RDAG (restricted directed acyclic graph) models. If two vertices or ed…
Toric invariant theory for maximum likelihood estimation in log-linear models
Carlos Améndola, Kathlén Kohn, Philipp Reichenbach +1
We establish connections between invariant theory and maximum likelihood estimation for discrete statistical models. We show that norm minimization over a torus orbit is equivalent…
Invariant theory and scaling algorithms for maximum likelihood estimation
Carlos Améndola, Kathlén Kohn, Philipp Reichenbach +1
We uncover connections between maximum likelihood estimation in statistics and norm minimization over a group orbit in invariant theory. We focus on Gaussian transformation familie…