1 citations · 1 across the 7 of their papers we have counts for
7 papers
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning
Ruichu Cai, Junjie Wan, Weilin Chen +4
Estimating long-term causal effects by combining long-term observational and short-term experimental data is a crucial but challenging problem in many real-world scenarios. In exis…
Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination
Weilin Chen, Ruichu Cai, Junjie Wan +2
Long-term causal inference has drawn increasing attention in many scientific domains. Existing methods mainly focus on estimating average long-term causal effects by combining long…
Targeted Regularization for Causal Effect Estimation with Exponential Dispersion Family Outcomes
Jiahong Li, Zeqin Yang, Jixing Xu +4
Neural Networks (NNs) for causal effect estimation have shown strong empirical performance, yet endowing them with desirable semiparametric properties -- doubly robustness and fast…
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights
Zeqin Yang, Weilin Chen, Ruichu Cai +7
Long-term treatment effect estimation is a significant but challenging problem in many applications. Existing methods rely on ideal assumptions, such as no unobserved confounders o…
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
Weilin Chen, Ruichu Cai, Zeqin Yang +4
Causal effect estimation under networked interference is an important but challenging problem. Available parametric methods are limited in their model space, while previous semipar…
Generalization bound for estimating causal effects from observational network data
Ruichu Cai, Zeqin Yang, Weilin Chen +2
Estimating causal effects from observational network data is a significant but challenging problem. Existing works in causal inference for observational network data lack an analys…
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…