Stable Prediction across Unknown Environments. - Kun Kuang; Peng Cui 001; Susan Athey; Ruoxuan Xiong; Bo Li 064 (KDD, 2018)

A tractable ellipsoidal approximation for voltage regulation problems. - Pan Li 004; Baihong Jin; Ruoxuan Xiong; Dai Wang; Alberto L. Sangiovanni-Vincentelli; Baosen Zhang (ACC, 2019)

Stable Prediction with Model Misspecification and Agnostic Distribution Shift. - Kun Kuang; Ruoxuan Xiong; Peng Cui 001; Susan Athey; Bo Li 064 (AAAI, 2020)

Federated Causal Inference in Heterogeneous Observational Data. - Ruoxuan Xiong; Allison Koenecke; Michael A. Powell; Zhu Shen; Joshua T. Vogelstein; Susan Athey (CoRR, 2021)

Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization. - Junkun Yuan; Xu Ma; Kun Kuang; Ruoxuan Xiong; Mingming Gong; Lanfen Lin (CoRR, 2021)

Treatment Effect Estimation with Unmeasured Confounders in Data Fusion. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Minqing Zhu; Yuxuan Liu; Bo Li 064; Furui Liu; Zhihua Wang 008; Fei Wu 001 (CoRR, 2022)

Learning Individual Treatment Effects under Heterogeneous Interference in Networks. - Ziyu Zhao 001; Kun Kuang; Ruoxuan Xiong; Fei Wu 001 (CoRR, 2022)

Confounder Balancing for Instrumental Variable Regression with Latent Variable. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Fei Wu 001 (CoRR, 2022)

Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Minqing Zhu; Yuxuan Liu; Bo Li 064; Furui Liu; Zhihua Wang 008; Fei Wu 001 (AAAI, 2023)

Stable Estimation of Heterogeneous Treatment Effects. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Fei Wu 001 (ICML, 2023)

Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments. - Ruoxuan Xiong; Alex Chin; Sean J. Taylor (CDPD, 2023)

Instrumental Variable-Driven Domain Generalization with Unobserved Confounders. - Junkun Yuan; Xu Ma; Ruoxuan Xiong; Mingming Gong; Xiangyu Liu; Fei Wu 001; Lanfen Lin; Kun Kuang (ACM Trans. Knowl. Discov. Data, 2023)

Stable Prediction With Leveraging Seed Variable. - Kun Kuang; Haotian Wang 001; Yue Liu; Ruoxuan Xiong; Runze Wu 001; Weiming Lu 001; Yueting Zhuang; Fei Wu 001; Peng Cui 001; Bo Li 064 (IEEE Trans. Knowl. Data Eng., 2023)

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Xiaoqing Yang; Xuan Qin; Peng Zhen 001; Jiecheng Guo; Fei Wu 001; Kun Kuang (AAAI, 2024)

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. - Baohong Li; Haoxuan Li 001; Ruoxuan Xiong; Anpeng Wu; Fei Wu 001; Kun Kuang (ICML, 2024)

Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias. - Baohong Li; Anpeng Wu; Ruoxuan Xiong; Kun Kuang (ICML, 2024)

Higher-Order Causal Message Passing for Experimentation with Complex Interference. - Mohsen Bayati; Yuwei Luo; William Overman; Mohamad Sadegh Shirani Faradonbeh; Ruoxuan Xiong (NeurIPS, 2024)

Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. - Yingrong Wang; Anpeng Wu; Haoxuan Li 001; Weiming Liu 005; Qiaowei Miao; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs. - Ruoxuan Xiong; Alex Chin; Sean J. Taylor (CoRR, 2024)

Causal Inference with Complex Treatments: A Survey. - Yingrong Wang; Haoxuan Li 001; Minqin Zhu; Anpeng Wu; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Xiangwei Chen; Zexu Sun; Fei Wu 001; Kun Zhang 001 (CoRR, 2024)

Higher-Order Causal Message Passing for Experimentation with Complex Interference. - Mohsen Bayati; Yuwei Luo; William Overman; Sadegh Shirani; Ruoxuan Xiong (CoRR, 2024)

Optimal Experimental Design for Staggered Rollouts. - Ruoxuan Xiong; Susan Athey; Mohsen Bayati; Guido Imbens (Manag. Sci., 2024)

Learning Individual Treatment Effects under Heterogeneous Interference in Networks. - Ziyu Zhao 001; Yuqi Bai; Ruoxuan Xiong; Qingyu Cao; Chao Ma 009; Ning Jiang; Fei Wu 001; Kun Kuang (ACM Trans. Knowl. Discov. Data, 2024)

Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference. - Anpeng Wu; Haiyi Qiu; Zhengming Chen; Zijian Li 001; Ruoxuan Xiong; Fei Wu 001; Kun Zhang 001 (ICLR, 2025)

Learning double balancing representation for heterogeneous dose-response curve estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Fei Wu 001; Kun Kuang (Neural Networks, 2025)

Can We Validate Counterfactual Estimations in the Presence of General Network Interference? - Sadegh Shirani; Yuwei Luo; William Overman; Ruoxuan Xiong; Mohsen Bayati (CoRR, 2025)

Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. - Ziyu Zhao 001; Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Zhihua Wang 008; Fei Wu 001 (IEEE Trans. Knowl. Data Eng., 2025)

Sequential Treatment Effect Estimation with Unmeasured Confounders. - Yingrong Wang; Anpeng Wu; Baohong Li; Ziyang Xiao; Ruoxuan Xiong; Qing Han; Kun Kuang (CoRR, 2025)

Instrumental Variables in Causal Inference and Machine Learning: A Survey. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Fei Wu 001 (ACM Comput. Surv., 2025)