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Jan, 2024
条件熵的因果分层
Causal Layering via Conditional Entropy
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Itai Feigenbaum, Devansh Arpit, Huan Wang, Shelby Heinecke, Juan Carlos Niebles...
TL;DR
从可观测数据中,通过条件熵预言的方式,我们提供了一种恢复图层次结构的方法,以离散分布为前提,并以删除图中源或汇的方法来验证算法的正确性和纠正性。
Abstract
causal discovery
aims to recover information about an unobserved causal graph from the observable data it generates.
layerings
are orderings of the variables which place causes before effects. In this paper, we p
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