Causal inference necessarily relies upon untestable assumptions; hence, it is crucial to assess the robustness of obtained results to …

We present a method to construct confidence intervals for causal effects in a linear structural equation model that accounts for the uncertainty stemming from the causal discovery of the DAG.

Detecting influential features in non-linear and/or high-dimensional data is a challenging and increasingly important task in machine …