Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models

arXiv:2402.14777v1 Announce Type: cross
Abstract: We consider the task of causal imputation, where we aim to predict the outcomes of some set of actions across a wide range of possible contexts. As a running example, we consider predicting how different drugs affect cells from different cell types. We study the index-only setting, where the actions and contexts are categorical variables with a finite number of possible values. Even in this simple setting, a practical challenge arises, since often only a …

abstract aim arxiv cells counterfactual cs.lg drugs example graphs imputation running set stat.ml study type types