[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"

AAAI 22 - Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks

Code for TEDVAE, a VAE-based treatment effect estimation algorithm.

The official code of "Adversarial Counterfactual Environment Model Learning" (NeurIPS'23 spotlight)

Causal weights for macroeconomic shocks

Implementation for the paper: "Detecting critical treatment effect bias in small subgroups"

Applying AI to medical use cases: Diagnoses of lung and brain disorders, Building risk models and survival estimators for heart disease via RF, and Using NLP to extract information from radiology reports.