6 citations · 6 across the 1 of their papers we have counts for
2 papers
stat.ME2020★ 6 cited
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models
Imke Mayer, Julie Josse, Félix Raimundo +1
Inferring causal effects of a treatment, intervention or policy from observational data is central to many applications. However, state-of-the-art methods for causal inference seld…
stat.ME2019
Doubly robust treatment effect estimation with missing attributes
Imke Mayer, Erik Sverdrup, Tobias Gauss +3
Missing attributes are ubiquitous in causal inference, as they are in most applied statistical work. In this paper, we consider various sets of assumptions under which causal infer…