Meta learning for causal direction

The inaccessibility of controlled randomized trials due to inherent constraints in many fields of science has been a fundamental issue in causal inference. In this paper, we focus on distinguishing the cause from effect in the bivariate setting under limited observational data. Based on recent devel...

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Detalles Bibliográficos
Main Authors: Ton, J-F, Sejdinovic, D, Fukumizu, K
Formato: Conference item
Idioma:English
Publicado: Association for the Advancement of Artificial Intelligence 2021