Combining Interventional and Observational Data Using Causal Reductions

Maximilian Ilse, Patrick Forré, Max Welling +1

Unobserved confounding is one of the main challenges when estimating causal effects. We propose a causal reduction method that, given a causal model, replaces an arbitrary number o…