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Exogenous Isomorphism for Counterfactual Identifiability

  • Yikang Chen
  • , Dehui Du*
  • *此作品的通讯作者
  • East China Normal University

科研成果: 期刊稿件会议文章同行评审

摘要

This paper investigates ~L3-identifiability, a form of complete counterfactual identifiability within the Pearl Causal Hierarchy (PCH) framework, ensuring that all Structural Causal Models (SCMs) satisfying the given assumptions provide consistent answers to all causal questions. To simplify this problem, we introduce exogenous isomorphism and propose ~EI-identifiability, reflecting the strength of model identifiability required for ~L3-identifiability. We explore sufficient assumptions for achieving ~EI-identifiability in two special classes of SCMs: Bijective SCMs (BSCMs), based on counterfactual transport, and Triangular Monotonic SCMs (TM-SCMs), which extend ~L2-identifiability. Our results unify and generalize existing theories, providing theoretical guarantees for practical applications. Finally, we leverage neural TM-SCMs to address the consistency problem in counterfactual reasoning, with experiments validating both the effectiveness of our method and the correctness of the theory.

源语言英语
页(从-至)8022-8064
页数43
期刊Proceedings of Machine Learning Research
267
出版状态已出版 - 2025
活动42nd International Conference on Machine Learning, ICML 2025 - Vancouver, 加拿大
期限: 13 7月 202519 7月 2025

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