5 citations · 9 across the 10 of their papers we have counts for
3 papers · 1 filter
Asymptotics of Nonparametric Estimation under General Non-monotone MAR Missingness: A Nonparametric Maximum Likelihood Approach
Yating Zou, Huimin Hu, Jeffrey Näf +1
Missing data are pervasive in empirical research, and the missing at random (MAR) condition has been central to their analysis since its introduction fifty years ago. Yet theoretic…
Generative Modeling under Non-Monotone MAR Missingness via Approximate Wasserstein Gradient Flows
Gitte Kremling, Jeffrey Näf, Johannes Lederer
The prevalence of missing values in data science poses a substantial risk to any further analyses. Despite a wealth of research, principled nonparametric methods to deal with gener…
CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
Jeffrey Näf, Riana Valera Mbelson, Markus Meierer
Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual settings, yet existing approaches…