Amir-Hossein Karimi

Probabilistic Counterfactual Inference for Discrete Outcomes in Gaussian-Process Causal Models

Counterfactual inference in Gaussian-process structural causal models (GP-SCMs) has been developed primarily for continuous endogenous variables, limiting applicability to causal graphs that contain discrete child nodes with continuous parents. We introduce a unified probabilistic framework for counterfactual inference...