Xie, Feng

22 publications

ICML 2025 Causal Attribution Analysis for Continuous Outcomes Shanshan Luo, Yu Yixuan, Chunchen Liu, Feng Xie, Zhi Geng

ICML 2025 Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects Models Xichen Guo, Feng Xie, Yan Zeng, Hao Zhang, Zhi Geng

ICML 2025 Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations Zhengming Chen, Yewei Xia, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai, Kun Zhang

IJCAI 2025 Identifying Causal Mechanism Shifts Under Additive Models with Arbitrary Noise Yewei Xia, Xueliang Cui, Hao Zhang, Yixin Ren, Feng Xie, Jihong Guan, Ruxin Wang, Shuigeng Zhou

ICML 2025 Local Identifying Causal Relations in the Presence of Latent Variables Zheng Li, Zeyu Liu, Feng Xie, Hao Zhang, Chunchen Liu, Zhi Geng

NeurIPS 2025 Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables Zheng Li, Xichen Guo, Feng Xie, Yan Zeng, Hao Zhang, Zhi Geng

ICML 2024 Automating the Selection of Proxy Variables of Unmeasured Confounders Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng

JMLR 2024 Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang

NeurIPS 2024 Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments Feng Xie, Zhen Yao, Lin Xie, Yan Zeng, Zhi Geng

NeurIPS 2024 Learning Discrete Latent Variable Structures with Tensor Rank Conditions Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang

ICML 2024 Local Causal Structure Learning in the Presence of Latent Variables Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng

ICML 2024 Policy Learning for Balancing Short-Term and Long-Term Rewards Peng Wu, Ziyu Shen, Feng Xie, Wang Zhongyao, Chunchen Liu, Yan Zeng

ICLR 2024 Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang

NeurIPS 2023 Identification of Nonlinear Latent Hierarchical Models Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang

IJCAI 2023 Some General Identification Results for Linear Latent Hierarchical Causal Structure Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai

ECML-PKDD 2022 EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting Feng Xie, Zhong Zhang, Liang Li, Bin Zhou, Yusong Tan

AAAI 2022 Identification of Linear Latent Variable Model with Arbitrary Distribution Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai

ICML 2022 Identification of Linear Non-Gaussian Latent Hierarchical Structure Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang

NeurIPS 2022 Latent Hierarchical Causal Structure Discovery with Rank Constraints Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang

IJCAI 2021 Causal Discovery with Multi-Domain LiNGAM for Latent Factors Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao

NeurIPS 2020 Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang

NeurIPS 2019 Triad Constraints for Learning Causal Structure of Latent Variables Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang