3 citations · 4 across the 4 of their papers we have counts for
4 papers
Proxy-Guided Measurement Calibration
Saketh Vishnubhatla, Shu Wan, Andre Harrison +2
Aggregate outcome variables collected through surveys and administrative records are often subject to systematic measurement error. For instance, in disaster loss databases, county…
Spatio-temporal Causal Learning for Streamflow Forecasting
Shu Wan, Reepal Shah, Qi Deng +3
Streamflow plays an essential role in the sustainable planning and management of national water resources. Traditional hydrologic modeling approaches simulate streamflow by establi…
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…
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…