March 13, 2024, 4:43 a.m. | Usef Faghihi, Amir Saki

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.07745v1 Announce Type: cross
Abstract: Let $X$ and $Z$ be random vectors, and $Y=g(X,Z)$. In this paper, on the one hand, for the case that $X$ and $Z$ are continuous, by using the ideas from the total variation and the flux of $g$, we develop a point of view in causal inference capable of dealing with a broad domain of causal problems. Indeed, we focus on a function, called Probabilistic Easy Variational Causal Effect (PEACE), which can measure the direct …

abstract arxiv case causal causal inference continuous cs.ai cs.lg easy ideas inference paper random stat.ml total type variation vectors view

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