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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…
stat.ME2026
Cost-Aware Optimized Front-Door Experimental Design
Leopold Mareis, Mathias Drton
Causal effect estimation often succeeds cost-constrained sequential data collection. This work considers multivariate linear front-door models with arbitrary unobserved confounding…