4 citations · 6 across the 3 of their papers we have counts for
3 papers
stat.ME2022★ 4 cited
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data
Yuxuan Zhao, Alex Townsend, Madeleine Udell
Many real-world datasets contain missing entries and mixed data types including categorical and ordered (e.g. continuous and ordinal) variables. Imputing the missing entries is nec…
stat.ME2022★ 2 cited
gcimpute: A Package for Missing Data Imputation
Yuxuan Zhao, Madeleine Udell
This article introduces the Python package gcimpute for missing data imputation. gcimpute can impute missing data with many different variable types, including continuous, binary,…
cs.LG2020
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula
Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman +1
Missing value imputation is crucial for real-world data science workflows. Imputation is harder in the online setting, as it requires the imputation method itself to be able to evo…