Generalized Random Forests, Susan Athey, Julie Tibshirani, Stefan Wager, 2019Ann. Statist., Vol. 47DOI: 10.1214/18-AOS1709 - Introduces Generalized Random Forests, including Causal Forests, for heterogeneous treatment effect estimation.
Double/debiased machine learning for treatment and causal parameters, Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney K. Newey, James M. Robins, 2018The Econometrics Journal, Vol. 21DOI: 10.1111/ectj.12097 - Presents the Double Machine Learning framework for robust and debiased estimation of causal parameters, applicable to ATE and CATE.