3 papers
stat.ME2026
Emputation: Identification-Guided Neural Imputation Framework
Yanjiao Yang, Yikun Zhang, Xinwei Shen +1
We propose Emputation, a deep generative framework for learning imputation models. Emputation targets the extrapolation distribution of missing variables given observed variables,…
stat.ME2025
Masking criteria for selecting an imputation model
Yanjiao Yang, Daniel Suen, Yen-Chi Chen
The masking-one-out (MOO) procedure, masking an observed entry and comparing it versus its imputed values, is a very common procedure for comparing imputation models. We study the…
stat.ME2025
Markov Missing Graph: A Graphical Approach for Missing Data Imputation
Yanjiao Yang, Yen-Chi Chen
We introduce the Markov missing graph (MMG), a novel framework that imputes missing data based on undirected graphs. MMG leverages conditional independence relationships to locally…