A common problem in many modern statistical applications is to find a set of important variables—from a pool of many candidates—that explain the response of interest. For this task, model-X knockoffs offers a general framework that can leverage any feature importance measure to produce a variable selection algorithm: it discovers true effects while rigorously controlling the number or fraction of...