AINeutralarXiv – CS AI · Mar 27/1013
🧠
Causal Identification from Counterfactual Data: Completeness and Bounding Results
Researchers developed the CTFIDU+ algorithm for causal identification using counterfactual data, establishing theoretical limits for exact causal inference in non-parametric settings. The work extends previous completeness results by incorporating Layer 3 counterfactual distributions that can be experimentally obtained, and provides novel bounds for non-identifiable quantities.