4 papers
Where the Data End and the Mechanism Begins: Doubly Robust Causal Digital Twins for Treatment Strategies
Cong Cao
Digital twins are increasingly used to ask how a patient's health would evolve under alternative treatment strategies. When a twin couples a mechanistic model with learned componen…
When Reconstruction Is Not Enough: Doubly Robust Counterfactual and Interventional Mediation Analysis with Learned Multimodal Representations
Cong Cao
Learned representations of high-dimensional multimodal health records are increasingly used to adjust for confounding, yet they are usually trained to reconstruct the data rather t…
When Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation
Cong Cao
Prediction error is widely used to evaluate nuisance-function estimators in causal inference, but its relationship with the performance of the resulting causal estimator is not wel…
Causal Inference under Interference with Learned Exposure Mappings
Cong Cao
Exposure mappings are often assumed to be known in causal spillover analyses. In environmental settings, however, they are typically induced by transport processes that are not dir…