The Do-Calculus Revisited
arXiv:1210.4852
Abstract
The do-calculus was developed in 1995 to facilitate the identification of causal effects in non-parametric models. The completeness proofs of [Huang and Valtorta, 2006] and [Shpitser and Pearl, 2006] and the graphical criteria of [Tian and Shpitser, 2010] have laid this identification problem to rest. Recent explorations unveil the usefulness of the do-calculus in three additional areas: mediation analysis [Pearl, 2012], transportability [Pearl and Bareinboim, 2011] and metasynthesis. Meta-synthesis (freshly coined) is the task of fusing empirical results from several diverse studies, conducted on heterogeneous populations and under different conditions, so as to synthesize an estimate of a causal relation in some target environment, potentially different from those under study. The talk surveys these results with emphasis on the challenges posed by meta-synthesis. For background material, see http://bayes.cs.ucla.edu/csl_papers.html
Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012)
References in corpus (1)
Cited by in corpus (9)
- Neural Network Attributions: A Causal Perspective
- Causal Inference in Travel Demand Modeling (and the lack thereof)
- Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
- DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
- Causal analysis, Correlation-Response and Dynamic cavity
- Unsuitability of NOTEARS for Causal Graph Discovery
- Counterfactual Policy Evaluation for Decision-Making in Autonomous Driving
- Computational Causal Inference
- Causal Inference in medicine and in health policy, a summary