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Ditch the cross-world counterfactuals: Sequential Transport offers a DAG-aware, optimal transport approach to causal mediation analysis, providing deterministic counterfactual mediators and fine-grained attribution.
Decomposing probabilistic scores reveals exactly how much information is lost when a predictor simplifies the input data, offering a new lens for understanding calibration and model aggregation.