3 papers
math.ST2026
Asymptotics for Model Selection in Probabilistic Principal Component Analysis
Mathias Drton, Andrew McCormack, Daniel Windisch
The probabilistic formulation of principal component analysis promises statistically grounded solutions to the problem of selecting the number of principal components. However, dev…
math.PR2026
On the Uniqueness of Fréchet Means for Polytope Norms
Roan Talbut, Andrew McCormack, Anthea Monod
Fréchet means are a popular type of average for non-Euclidean datasets, defined as those points which minimise the average squared distance to a set of data points. We consider the…
stat.ML2025
Robust Score Matching
Richard Schwank, Andrew McCormack, Mathias Drton
Proposed in Hyvärinen (2005), score matching is a parameter estimation procedure that does not require computation of distributional normalizing constants. In this work we utilize…