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The Connection Between Causal Discovery and Downstream Machine Learning
The trend that I saw was actually connecting the learning of causal structure to downstream machine learning tasks. For example, as paper called on the generalization and adaptation performance of causal models. This is using an idea from causal inference called independence of mechanism. And so they use that intuition to basically say, well, the more right my graph is, the faster it should adapt to the new data set.