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Counterfactual Transportability: A Formal Approach
International Conference on Machine Learning
Generalizing causal knowledge across environments is a common challenge shared across many of the data-driven disciplines, including AI and ML. Experiments are usually performed in one environment (e.g., in a lab, on Earth, in a training ground), almost invariably, with the intent of being used elsewhere (e.g., outside the lab, on Mars, in the real world), in an environment that is related but somewhat different than the original one, where certain conditions and mechanisms are likely todblp:conf/icml/CorreaLB22 fatcat:jvnzp2axavhk5lku3tv4pqfpjy