Feb. 9, 2024, 5:44 a.m. | Heyang Gong

cs.LG updates on arXiv.org arxiv.org

In the realm of causal inference, Potential Outcomes (PO) and Structural Causal Models (SCM) are recognized as the principal frameworks.However, when it comes to Layer 3 valuations -- counterfactual queries deeply entwined with individual-level semantics -- both frameworks encounter limitations due to the degenerative issues brought forth by the consistency rule. This paper advocates for the Distribution-consistency Structural Causal Models (DiscoSCM) framework as a pioneering approach to counterfactual inference, skillfully integrating the strengths of both PO and SCM. The DiscoSCM …

causal inference counterfactual cs.ai cs.lg frameworks inference layer limitations scm semantics stat.me valuations

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