May 27, 2024, 4:45 a.m. | Alexis Bellot

cs.LG updates on

arXiv:2311.07259v2 Announce Type: replace-cross
Abstract: Predicting the effect of unseen interventions is a fundamental research question across the data sciences. It is well established that in general such questions cannot be answered definitively from observational data. This realization has fuelled a growing literature introducing various identifying assumptions, for example in the form of a causal diagram among relevant variables. In practice, this paradigm is still too rigid for many practical applications as it is generally not possible to confidently delineate …

abstract arxiv assumptions causal cs.lg data effects example form fundamental general literature markov question questions replace research type

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