2 papers
stat.ML2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
When a missing process depends on the missing values themselves, it needs to be explicitly modelled and taken into account while doing likelihood-based inference. We present an app…
stat.ML2019
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
Niels Bruun Ipsen, Lars Kai Hansen
How does missing data affect our ability to learn signal structures? It has been shown that learning signal structure in terms of principal components is dependent on the ratio of…