3 papers
stat.ME2026
Inverse Probability Weighting in a Post-Bayesian World
Owen Thomas, William Denault, Valeria Vitelli
We present a justification of the use of Inverse Probability Weighting (IPW) in a post-Bayesian framework, in which the bias-correction provided by IPW in a frequentist context is…
stat.ML2026
Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression
William R. P. Denault
Sparse linear regression is a fundamental tool in data analysis. However, traditional approaches often fall short when covariates exhibit structure or arise from heterogeneous sour…
stat.ME2025
Covariate-moderated Empirical Bayes Matrix Factorization
William R. P. Denault, Karl Tayeb, Peter Carbonetto +2
Matrix factorization is a fundamental method in statistics and machine learning for inferring and summarizing structure in multivariate data. Modern data sets often come with "side…