Identification of Linear Latent Variable Model with Arbitrary Distribution. - Zhengming Chen 002; Feng Xie 002; Jie Qiao; Zhifeng Hao; Kun Zhang 001; Ruichu Cai (AAAI, 2022)

Identification of Linear Non-Gaussian Latent Hierarchical Structure. - Feng Xie 002; Biwei Huang; Zhengming Chen 002; Yangbo He; Zhi Geng; Kun Zhang 001 (ICML, 2022)

Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models. - Feng Xie 002; Yangbo He; Zhi Geng; Zhengming Chen 002; Ru Hou; Kun Zhang 001 (Entropy, 2022)

Some General Identification Results for Linear Latent Hierarchical Causal Structure. - Zhengming Chen 002; Feng Xie 002; Jie Qiao; Zhifeng Hao; Ruichu Cai (IJCAI, 2023)

Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions. - Feng Xie 002; Yan Zeng 002; Zhengming Chen 002; Yangbo He; Zhi Geng; Kun Zhang 001 (Neurocomputing, 2023)

Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model. - Jie Qiao; Zhengming Chen 002; Jianhua Yu; Ruichu Cai; Zhifeng Hao (AAAI, 2024)

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis. - Jie Qiao; Yu Xiang; Zhengming Chen 002; Ruichu Cai; Zhifeng Hao (AAAI, 2024)

Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. - Songyao Jin; Feng Xie 002; Guangyi Chen 002; Biwei Huang; Zhengming Chen 002; Xinshuai Dong; Kun Zhang 001 (ICLR, 2024)

Automating the Selection of Proxy Variables of Unmeasured Confounders. - Feng Xie 002; Zhengming Chen 002; Shanshan Luo; Wang Miao; Ruichu Cai; Zhi Geng (ICML, 2024)

Learning Discrete Latent Variable Structures with Tensor Rank Conditions. - Zhengming Chen 002; Ruichu Cai; Feng Xie 002; Jie Qiao; Anpeng Wu; Zijian Li 001; Zhifeng Hao; Kun Zhang 001 (NeurIPS, 2024)

When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting. - Zijian Li 001; Ruichu Cai; Zhenhui Yang; Haiqin Huang; Guangyi Chen 002; Yifan Shen 004; Zhengming Chen 002; Xiangchen Song; Zhifeng Hao; Kun Zhang 001 (CoRR, 2024)

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. - Feng Xie 002; Biwei Huang; Zhengming Chen 002; Ruichu Cai; Clark Glymour; Zhi Geng; Kun Zhang 001 (J. Mach. Learn. Res., 2024)

Rank Constraints of High-Order Cumulants for Learning Linear Non-Gaussian Latent Polytree. - Ruichu Cai; Ying Shen; Zhengming Chen 002; Feng Xie 002; Yu Xiang; Zhifeng Hao (CSCWD, 2025)

Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference. - Anpeng Wu; Haiyi Qiu; Zhengming Chen 002; Zijian Li 001; Ruoxuan Xiong; Fei Wu 001; Kun Zhang 001 (ICLR, 2025)

Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations. - Zhengming Chen 002; Yewei Xia; Feng Xie 002; Jie Qiao; Zhifeng Hao; Ruichu Cai; Kun Zhang 001 (ICML, 2025)

Extracting Rare Dependence Patterns via Adaptive Sample Reweighting. - Yiqing Li; Yewei Xia; Xiaofei Wang; Zhengming Chen 002; Liuhua Peng; Mingming Gong; Kun Zhang 001 (ICML, 2025)

Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism. - Ruichu Cai; Kaitao Zheng; Junxian Huang 002; Zijian Li 001; Zhengming Chen 002; Boyan Xu; Zhifeng Hao (IJCAI, 2025)

Testing Conditional Independence Between Latent Variables by Independence Residuals. - Zhengming Chen 002; Jie Qiao; Feng Xie 002; Ruichu Cai; Zhifeng Hao; Keli Zhang (IEEE Trans. Neural Networks Learn. Syst., 2025)