4 papers
Distribution Shift in Missing Data Imputation: A Risk-Based Perspective and Importance-Weighted Correction under MAR
Luke Shannon, Song Liu, Katarzyna Reluga
Missing data imputation, where a model is trained on observed data to estimate unobserved values, is a fundamental problem in machine learning. In this paper, we rigorously formula…
Direct Doubly Robust Estimation of Conditional Quantile Contrasts
Josh Givens, Song Liu, Henry W J Reeve +1
Within heterogeneous treatment effect (HTE) analysis, various estimands have been proposed to capture the effect of a treatment conditional on covariates. Recently, the conditional…
Score Matching With Missing Data
Josh Givens, Song Liu, Henry W J Reeve
Score matching is a vital tool for learning the distribution of data with applications across many areas including diffusion processes, energy based modelling, and graphical model…
Conditional Outcome Equivalence: A Quantile Alternative to CATE
Josh Givens, Henry W J Reeve, Song Liu +1
Conditional quantile treatment effect (CQTE) can provide insight into the effect of a treatment beyond the conditional average treatment effect (CATE). This ability to provide info…