An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data. - Ruichu Cai; Feng Xie 002; Wei Chen 103; Zhifeng Hao (IWQoS, 2017)

Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples. - Feng Xie 002; Ruichu Cai; Yan Zeng 002; Zhifeng Hao (IScIDE (2), 2019)

Triad Constraints for Learning Causal Structure of Latent Variables. - Ruichu Cai; Feng Xie 002; Clark Glymour; Zhifeng Hao; Kun Zhang 001 (NeurIPS, 2019)

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. - Feng Xie 002; Ruichu Cai; Biwei Huang; Clark Glymour; Zhifeng Hao; Kun Zhang 001 (NeurIPS, 2020)

Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs. - Feng Xie 002; Ruichu Cai; Biwei Huang; Clark Glymour; Zhifeng Hao; Kun Zhang 001 (CoRR, 2020)

Mining hidden non-redundant causal relationships in online social networks. - Wei Chen 103; Ruichu Cai; Zhifeng Hao; Chang Yuan; Feng Xie 002 (Neural Comput. Appl., 2020)

A causal discovery algorithm based on the prior selection of leaf nodes. - Yan Zeng 002; Zhifeng Hao; Ruichu Cai; Feng Xie 002; Liang Ou; Ruihui Huang (Neural Networks, 2020)

An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables. - Feng Xie 002; Ruichu Cai; Yan Zeng 002; Jiantao Gao; Zhifeng Hao (IEEE Trans. Neural Networks Learn. Syst., 2020)

Causal Discovery with Multi-Domain LiNGAM for Latent Factors. - Yan Zeng 002; Shohei Shimizu; Ruichu Cai; Feng Xie 002; Michio Yamamoto; Zhifeng Hao (IJCAI, 2021)

Identification of Linear Latent Variable Model with Arbitrary Distribution. - Zhengming Chen; 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; Yangbo He; Zhi Geng; Kun Zhang 001 (ICML, 2022)

Latent Hierarchical Causal Structure Discovery with Rank Constraints. - Biwei Huang; Charles Jia Han Low; Feng Xie 002; Clark Glymour; Kun Zhang 001 (NeurIPS, 2022)

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

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

Identification of Nonlinear Latent Hierarchical Models. - Lingjing Kong; Biwei Huang; Feng Xie 002; Eric P. Xing; Yuejie Chi; Kun Zhang 001 (NeurIPS, 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; Yangbo He; Zhi Geng; Kun Zhang 001 (Neurocomputing, 2023)

Nonlinear Causal Discovery for High-Dimensional Deterministic Data. - Yan Zeng 002; Zhifeng Hao; Ruichu Cai; Feng Xie 002; Libo Huang; Shohei Shimizu (IEEE Trans. Neural Networks Learn. Syst., 2023)

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; Xinshuai Dong; Kun Zhang 001 (ICLR, 2024)

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

Policy Learning for Balancing Short-Term and Long-Term Rewards. - Peng Wu 012; Ziyu Shen; Feng Xie 002; Zhongyao Wang; Chunchen Liu; Yan Zeng 002 (ICML, 2024)

Local Causal Structure Learning in the Presence of Latent Variables. - Feng Xie 002; Zheng Li; Peng Wu 012; Yan Zeng 002; Chunchen Liu; Zhi Geng (ICML, 2024)

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

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. - Feng Xie 002; Biwei Huang; Zhengming Chen; 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; Feng Xie 002; Yu Xiang; Zhifeng Hao (CSCWD, 2025)

Regression-based conditional independence test with adaptive kernels. - Yixin Ren; Juncai Zhang; Yewei Xia; Ruxin Wang 001; Feng Xie 002; Jihong Guan; Hao Zhang 079; Shuigeng Zhou (Artif. Intell., 2025)

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

Confounded Causal Imitation Learning with Instrumental Variables. - Yan Zeng 002; Shenglan Nie; Feng Xie 002; Libo Huang; Peng Wu 012; Zhi Geng (CoRR, 2025)