Estimating heterogeneous treatment effects with right-censored data via causal survival forests. - Yifan Cui 001; Michael R. Kosorok; Stefan Wager; Ruoqing Zhu (CoRR, 2020)

Dimension Reduction Forests: Local Variable Importance Using Structured Random Forests. - Joshua Daniel Loyal; Ruoqing Zhu; Yifan Cui 001; Xin Zhang (J. Comput. Graph. Stat., 2022)

Proximal Causal Learning of Conditional Average Treatment Effects. - Erik Sverdrup; Yifan Cui 001 (ICML, 2023)

Pessimistic Model Selection for Offline Deep Reinforcement Learning. - Chao-Han Huck Yang; Zhengling Qi; Yifan Cui 001; Pin-Yu Chen (UAI, 2023)

Proximal Causal Learning of Heterogeneous Treatment Effects. - Erik Sverdrup; Yifan Cui 001 (CoRR, 2023)

Reinforcement Learning with Continuous Actions Under Unmeasured Confounding. - Yuhan Li; Eugene Han; Yifan Hu; Wenzhuo Zhou; Zhengling Qi; Yifan Cui 001; Ruoqing Zhu (CoRR, 2025)