Learning directed acyclic graphs (DAGs) to identify causal relations
und...
Causal inference is the process of using assumptions, study designs, and...
This paper studies the confounding effects from the unmeasured confounde...
In the presence of unmeasured confounders, we address the problem of
tre...
Influenced by the great success of deep learning via cloud computing and...
Instrumental variables (IVs), sources of treatment randomization that ar...
One fundamental problem in the learning treatment effect from observatio...