Search Results for author:
Found 2 papers, 0 papers with code
Non-parametric identifiability and sensitivity analysis of synthetic control models
While identifiability of the causal estimand in such models has been obtained from a range of assumptions, it is widely and implicitly assumed that the underlying assumptions are satisfied for all time periods both pre- and post-intervention.
Estimating Categorical Counterfactuals via Deep Twin Networks
To learn causal mechanisms satisfying these constraints, and perform counterfactual inference with them, we introduce deep twin networks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
