Valentyn Melnychuk

GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes

Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation

Efficient and Sharp Off-Policy Learning under Unobserved Confounding

IGC-Net for conditional average potential outcome estimation over time

An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes

Treatment Effect Estimation for Optimal Decision-Making

Differentially private learners for heterogeneous treatment effects

Conformal Prediction for Causal Effects of Continuous Treatments

Orthogonal Representation Learning for Estimating Causal Quantities

Conformal prediction for causal effects of continuous treatments

G-Transformer for Conditional Average Potential Outcome Estimation over Time

Counterfactual fairness prediction: Consistent estimation with generative models and theoretical guarantees