Understanding causal relationships lies at the heart of scientific inquiry. Across disciplines, from medicine and public health to economics (Card, 1993; Angrist and Krueger, 1991), social sciences (Rosenbaum and Rubin, 1983; Imbens, 2024), epidemiology (R ...
We address the problem of identifiability of an arbitrary conditional causal effect given both the causal graph and a set of any observational and/or interventional distributions of the form Q[S] :" P p(S|do(V/S)), where V denotes the set of all observed v ...
We study the problem of assortative and disassortative partitions on random dregular graphs. Nodes in the graph are partitioned into two non-empty groups. In the assortative partition every node requires at least H of their neighbors to be in their own gro ...
We revisit the problem of general identifiability originally introduced in [Lee et al., 2019] for causal inference and note that it is necessary to add positivity assumption of observational distribution to the original definition of the problem. We show t ...
