Double Machine Learning Density Estimation for Local Treatment Effects with Instruments

no code implementations • NeurIPS 2021 • Yonghan Jung, Jin Tian, Elias Bareinboim

We study the problem of estimating the density of the causal effect of a binary treatment on a continuous outcome given a binary instrumental variable in the presence of covariates.

BIG-bench Machine Learning Density Estimation

Learning Causal Effects via Weighted Empirical Risk Minimization

no code implementations • NeurIPS 2020 • Yonghan Jung, Jin Tian, Elias Bareinboim

In this paper, we develop a learning framework that marries two families of methods, benefiting from the generality of the causal identification theory and the effectiveness of the estimators produced based on the principle of ERM.

Causal Identification Causal Inference