cross-fitting

Code for causal isotonic calibration for heterogeneous treatment effects (appeared in ICML, 2023)

Leakage-aware LendingClub default-risk prediction with logit, elastic net, CART, bagging, random forests, gains and lift screening, and cross-fitted DML.

Ensemble methods for learning features of heterogeneous treatment effects with valid downstream inference via repeated cross-fitting

Estimating causal treatment effects using Double Machine Learning (DoubleML), Interactive Regression Models, and Instrumental Variables with cross-fitting and orthogonalization

Code, Jupyter notebook and retained results for acquisition-level bridge monitoring on Z24, Route345 and openLAB: measurement-quality estimation, fault-aware classification, selective prediction, cross-fitting and instrumental verification. Companion repository for the ICAM3E 2026 study.

Double ML for time series data