3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation
Minqin Zhu, Anpeng Wu, Haoxuan Li +8
Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and management science. Most recent stu…
cs.LG2022★ 1 cited
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning
Ruichu Cai, Weilin Chen, Zeqin Yang +4
Estimating long-term causal effects based on short-term surrogates is a significant but challenging problem in many real-world applications, e.g., marketing and medicine. Despite i…
stat.ML2022★ 3 cited
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace
Shu Wan, Chen Zheng, Zhonggen Sun +4
Uplift modeling is a rapidly growing approach that utilizes causal inference and machine learning methods to directly estimate the heterogeneous treatment effects, which has been w…