15 citations · 16 across the 10 of their papers we have counts for
11 papers
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…
Thermodynamic Response Functions in Singular Bayesian Models
Sean Plummer
Singular statistical models-including mixtures, matrix factorization, and neural networks-violate regular asymptotics due to parameter non-identifiability and degenerate Fisher geo…
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…
Feasibility Preservation under Monotone Retrieval Truncation
Sean Plummer
Retrieval-based systems approximate access to a corpus by exposing only a truncated subset of available evidence. Even when relevant information exists in the corpus, truncation ca…