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  "Title": "Causal Discovery under a Confounder Blanket",
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  "Description": "Methods for learning causal relationships among a set of\nforeground variables X based on signals from a (potentially\nmuch larger) set of background variables Z, which are known\nnon-descendants of X. The confounder blanket learner (CBL) uses\nsparse regression techniques to simultaneously perform many\nconditional independence tests, with complementary pairs\nstability selection to guarantee finite sample error control.\nCBL is sound and complete with respect to a so-called \"lazy\noracle\", and works with both linear and nonlinear systems. For\ndetails, see Watson & Silva (2022) <arXiv:2205.05715>.",
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