Miriam Rateike

VACA: Designing Variational Graph Autoencoders for Causal Queries

In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the causal graph are available. Without making any parametric assumptions, VACA mimics the necessary properties of a Structura…