15 citations · 16 across the 10 of their papers we have counts for
4 papers · 2 filters
Decision-Sufficient Posterior Approximation
Sean Plummer
We investigate the consequences of requiring a posterior approximation to preserve a specified downstream decision problem. A target posterior and loss determine a regret geome…
Observable Geometry of Singular Statistical Models
Sean Plummer
Singular statistical models arise whenever different parameter values induce the same distribution, leading to non-identifiability and a breakdown of classical asymptotic theory. W…
Functional Bias and Tangent-Space Geometry in Variational Inference
Sean Plummer
Variational inference approximates Bayesian posterior distributions by projecting onto a tractable family of distributions. While most theoretical analyses evaluate the quality of…
Hypothesis Testing over Observable Regimes in Singular Models
Sean Plummer
Hypothesis testing in singular statistical models is often regarded as inherently problematic due to non-identifiability and degeneracy of the Fisher information. We show that the…