[ 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.

Causal weights for macroeconomic shocks

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

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.

"Causal Machine Learning for Cost-Effective Allocation of Electricity Aid" thesis for my Masters in Management and Digital Technologies at Ludwig-Maximillian Univeristy, Munich.