Ruoxuan Xiong

According to our database, Ruoxuan Xiong authored at least 38 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Causal Inference with Complex Treatments: A Survey.

Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Baohong Li, Keting Yin, Ruoxuan Xiong, Fei Wu, Kun Kuang

ACM Comput. Surv., July, 2026

Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness.

Zihan Liang, Ziwen Pan, Ruoxuan Xiong

CoRR, April, 2026

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models.

Hongyu Chen, David Simchi-Levi, Ruoxuan Xiong

CoRR, February, 2026

Pareto-optimal estimation and policy learning for balancing short-term and long-term outcomes.

Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Baohong Li, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang

Neural Networks, 2026

Continuous-Time Counterfactual Quantile Learning for Risk-Sensitive Policy Optimization.

Yi He, Anpeng Wu, Ruoxuan Xiong, Yingrong Wang, Kun Kuang

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025

Instrumental Variables in Causal Inference and Machine Learning: A Survey.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu

ACM Comput. Surv., November, 2025

Sequential Treatment Effect Estimation with Unmeasured Confounders.

Yingrong Wang, Anpeng Wu, Baohong Li, Ziyang Xiao, Ruoxuan Xiong, Qing Han, Kun Kuang

CoRR, May, 2025

Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders.

Ziyu Zhao, Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Zhihua Wang, Fei Wu

IEEE Trans. Knowl. Data Eng., February, 2025

Can We Validate Counterfactual Estimations in the Presence of General Network Interference?

Sadegh Shirani, Yuwei Luo, William Overman, Ruoxuan Xiong, Mohsen Bayati

CoRR, February, 2025

Learning double balancing representation for heterogeneous dose-response curve estimation.

Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Fei Wu, Kun Kuang

Neural Networks, 2025

Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation.

Minqin Zhu, Zexu Sun, Ruoxuan Xiong, Anpeng Wu, Baohong Li, Caizhi Tang, Jun Zhou, Fei Wu, Kun Kuang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments.

Baohong Li, Yingrong Wang, Anpeng Wu, Ming Ma, Ruoxuan Xiong, Kun Kuang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference.

Anpeng Wu, Haiyi Qiu, Zhengming Chen, Zijian Li, Ruoxuan Xiong, Fei Wu, Kun Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Causal Representation Learning from Multimodal Clinical Records under Non-Random Modality Missingness.

Zihan Liang, Ziwen Pan, Ruoxuan Xiong

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

2024

Learning Individual Treatment Effects under Heterogeneous Interference in Networks.

Ziyu Zhao, Yuqi Bai, Ruoxuan Xiong, Qingyu Cao, Chao Ma, Ning Jiang, Fei Wu, Kun Kuang

ACM Trans. Knowl. Discov. Data, September, 2024

Optimal Experimental Design for Staggered Rollouts.

Ruoxuan Xiong, Susan Athey, Mohsen Bayati, Guido Imbens

Manag. Sci., 2024

Higher-Order Causal Message Passing for Experimentation with Complex Interference.

Mohsen Bayati, Yuwei Luo, William Overman, Sadegh Shirani, Ruoxuan Xiong

CoRR, 2024

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Xiangwei Chen, Zexu Sun, Fei Wu, Kun Zhang

CoRR, 2024

Causal Inference with Complex Treatments: A Survey.

Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Ruoxuan Xiong, Fei Wu, Kun Kuang

CoRR, 2024

Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs.

Ruoxuan Xiong, Alex Chin, Sean J. Taylor

CoRR, 2024

Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects.

Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang

CoRR, 2024

Higher-Order Causal Message Passing for Experimentation with Complex Interference.

Mohsen Bayati, Yuwei Luo, William Overman, Mohamad Sadegh Shirani Faradonbeh, Ruoxuan Xiong

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias.

Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation.

Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Stable Prediction With Leveraging Seed Variable.

Kun Kuang, Haotian Wang, Yue Liu, Ruoxuan Xiong, Runze Wu, Weiming Lu, Yueting Zhuang, Fei Wu, Peng Cui, Bo Li

IEEE Trans. Knowl. Data Eng., June, 2023

Instrumental Variable-Driven Domain Generalization with Unobserved Confounders.

Junkun Yuan, Xu Ma, Ruoxuan Xiong, Mingming Gong, Xiangyu Liu, Fei Wu, Lanfen Lin, Kun Kuang

ACM Trans. Knowl. Discov. Data, 2023

Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments.

Ruoxuan Xiong, Alex Chin, Sean J. Taylor

Proceedings of the KDD'23 Workshop on Causal Discovery, 2023

Stable Estimation of Heterogeneous Treatment Effects.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

Proceedings of the International Conference on Machine Learning, 2023

Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Confounder Balancing for Instrumental Variable Regression with Latent Variable.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

CoRR, 2022

Learning Individual Treatment Effects under Heterogeneous Interference in Networks.

Ziyu Zhao, Kun Kuang, Ruoxuan Xiong, Fei Wu

CoRR, 2022

Treatment Effect Estimation with Unmeasured Confounders in Data Fusion.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu

CoRR, 2022

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

Federated Causal Inference in Heterogeneous Observational Data.

Ruoxuan Xiong, Allison Koenecke, Michael A. Powell, Zhu Shen, Joshua T. Vogelstein, Susan Athey

CoRR, 2021

2020

Stable Prediction with Model Misspecification and Agnostic Distribution Shift.

Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A tractable ellipsoidal approximation for voltage regulation problems.

Pan Li, Baihong Jin, Ruoxuan Xiong, Dai Wang, Alberto L. Sangiovanni-Vincentelli, Baosen Zhang

Proceedings of the 2019 American Control Conference, 2019

2018

Stable Prediction across Unknown Environments.

Kun Kuang, Peng Cui, Susan Athey, Ruoxuan Xiong, Bo Li

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018