Nested Counterfactual Identification from Arbitrary Surrogate Experiments
–Neural Information Processing Systems
In this paper, we study the identification of nested counterfactuals from an arbitrary combination of observations and experiments. Specifically, building on a more explicit definition of nested counterfactuals, we prove the counterfactual unnesting theorem (CUT), which allows one to map arbitrary nested counterfactuals to unnested ones.
Neural Information Processing Systems
Aug-14-2025, 04:00:32 GMT
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