Tara V Anand

5/8 “Causal Discovery over Clusters of Variables in Markovian Systems” (joint w/ @taravanand, @adelehr, Jin Tian, Gregory Hripcsak) Thu, 7:30 pm (#2601) Link: causalai.net/r128.pdf We study causal discovery when variables come grouped into clusters, a setting where standard algorithms often fail due to ambiguous independence patterns. We characterize the Markov equivalence classes of cluster DAGs (C-DAGs) and introduce CLOC, the first sound and complete constraint-based algorithm for discovering causal structure directly at the cluster level.

@yudapearl @AJAveritt @eliasbareinboim 1/C-DAGs address the problem of when only partial knowledge is available, such that a full causal diagram cannot be specified (particularly useful in high-dimensional domains, like medicine). Consider an example where the following edges are known:X→Y; Z1→X; Z1↔X; Z2→Y; Z2↔Y