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English(EN) On the Incompleteness of do-calculus for Universal Identifiability

新研究论文质疑do演算在因果效应识别上的完备性

一篇新的arXiv论文提出了do演算在因果效应识别中完备性的形式化定义。尽管现有研究已证明do演算在ID和gID等特定问题上是可靠且完备的,但这项工作表明它在通用可识别性(uID)等更一般的问题上是不完备的。该论文提出了完备性的严格形式化方法,并强调由于这一限制,uID问题仍然悬而未决。 AI

排序理由 该集群包含一篇讨论因果推断演算理论局限性的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.CL 阅读 →

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新研究论文质疑do演算在因果效应识别上的完备性

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该集群包含一篇讨论因果推断演算理论局限性的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yaroslav Kivva, Aliaksandra Novik, Negar Kiyavash ·

    关于do-calculus在通用可识别性上的不完备性

    arXiv:2611.08916v1 Announce Type: new Abstract: We study the problem of causal effect identification from an arbitrary set of observational and/or interventional distributions, which we call Universal Identifiability (uID). The uID problem generalizes existing classical identifia…