Demonstration of inferring causality from relational databases with CaRL
@article{Kayali2020DemonstrationOI,
title={Demonstration of inferring causality from relational databases with CaRL},
author={Moe Kayali and Babak Salimi},
journal={Proceedings of the VLDB Endowment},
year={2020},
volume={13},
pages={2985 - 2988}
}Understanding cause-and-effect is key for informed decision-making. The gold standard in causal inference is performing controlled experiments, which may not always be feasible due to ethical, legal, or cost constraints. As an alternative, inferring causality from observational data has been extensively used in statistics and social sciences. However, the existing methods critically rely on a restrictive assumption that the population of study consists of homogeneous units that can be…
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