Feng Xie - RankMe

45 papers A* 19B 1C 1Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Causal Attribution Analysis for Continuous Outcomes. ICML Shanshan Luo, Yixuan Yu, Chunchen Liu, Feng Xie, Zhi Geng
2025	J	`jnl`	Confounded Causal Imitation Learning with Instrumental Variables. CoRR Yan Zeng, Shenglan Nie, Feng Xie, Libo Huang, Peng Wu, Zhi Geng
2025	A*	`conf`	Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects Models. ICML Xichen Guo, Feng Xie, Yan Zeng, Hao Zhang, Zhi Geng
2025	A*	`conf`	Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations. ICML Zhengming Chen, Yewei Xia, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai, Kun Zhang
2025	A*	`conf`	Identifying Causal Mechanism Shifts Under Additive Models with Arbitrary Noise. IJCAI Yewei Xia, Xueliang Cui, Hao Zhang, Yixin Ren, Feng Xie, Jihong Guan, Ruxin Wang, Shuigeng Zhou
2025	A*	`conf`	Local Identifying Causal Relations in the Presence of Latent Variables. ICML Zheng Li, Zeyu Liu, Feng Xie, Hao Zhang, Chunchen Liu, Zhi Geng
2025	C	`conf`	Rank Constraints of High-Order Cumulants for Learning Linear Non-Gaussian Latent Polytree. CSCWD Ruichu Cai, Ying Shen, Zhengming Chen, Feng Xie, Yu Xiang, Zhifeng Hao
2025	J	`jnl`	Regression-based conditional independence test with adaptive kernels. Artif. Intell. Yixin Ren, Juncai Zhang, Yewei Xia, Ruxin Wang, Feng Xie, Jihong Guan, Hao Zhang, Shuigeng Zhou
2025	J	`jnl`	Testing Conditional Independence Between Latent Variables by Independence Residuals. IEEE Trans. Neural Networks Learn. Syst. Zhengming Chen, Jie Qiao, Feng Xie, Ruichu Cai, Zhifeng Hao, Keli Zhang
2024	A*	`conf`	Automating the Selection of Proxy Variables of Unmeasured Confounders. ICML Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng
2024	J	`jnl`	Automating the Selection of Proxy Variables of Unmeasured Confounders. CoRR Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng
2024	J	`jnl`	Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. J. Mach. Learn. Res. Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
2024	A*	`conf`	Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments. NeurIPS Feng Xie, Zhen Yao, Lin Xie, Yan Zeng, Zhi Geng
2024	J	`jnl`	Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments. CoRR Feng Xie, Zhen Yao, Lin Xie, Yan Zeng, Zhi Geng
2024	A*	`conf`	Learning Discrete Latent Variable Structures with Tensor Rank Conditions. NeurIPS Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang
2024	J	`jnl`	Learning Discrete Latent Variable Structures with Tensor Rank Conditions. CoRR Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang
2024	A*	`conf`	Local Causal Structure Learning in the Presence of Latent Variables. ICML Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng
2024	J	`jnl`	Local Causal Structure Learning in the Presence of Latent Variables. CoRR Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng
2024	J	`jnl`	Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables. CoRR Zheng Li, Feng Xie, Yan Zeng, Zhi Geng
2024	A*	`conf`	Policy Learning for Balancing Short-Term and Long-Term Rewards. ICML Peng Wu, Ziyu Shen, Feng Xie, Zhongyao Wang, Chunchen Liu, Yan Zeng
2024	J	`jnl`	Policy Learning for Balancing Short-Term and Long-Term Rewards. CoRR Peng Wu, Ziyu Shen, Feng Xie, Zhongyao Wang, Chunchen Liu, Yan Zeng
2024	A*	`conf`	Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. ICLR Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang
2024	J	`jnl`	Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models. CoRR Xichen Guo, Zheng Li, Biwei Huang, Yan Zeng, Zhi Geng, Feng Xie
2023	J	`jnl`	Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions. Neurocomputing Feng Xie, Yan Zeng, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang
2023	J	`jnl`	Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
2023	A*	`conf`	Identification of Nonlinear Latent Hierarchical Models. NeurIPS Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	J	`jnl`	Identification of Nonlinear Latent Hierarchical Models. CoRR Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	J	`jnl`	Nonlinear Causal Discovery for High-Dimensional Deterministic Data. IEEE Trans. Neural Networks Learn. Syst. Yan Zeng, Zhifeng Hao, Ruichu Cai, Feng Xie, Libo Huang, Shohei Shimizu
2023	A*	`conf`	Some General Identification Results for Linear Latent Hierarchical Causal Structure. IJCAI Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai
2022	A*	`conf`	Identification of Linear Latent Variable Model with Arbitrary Distribution. AAAI Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai
2022	A*	`conf`	Identification of Linear Non-Gaussian Latent Hierarchical Structure. ICML Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang
2022	A*	`conf`	Latent Hierarchical Causal Structure Discovery with Rank Constraints. NeurIPS Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
2022	J	`jnl`	Latent Hierarchical Causal Structure Discovery with Rank Constraints. CoRR Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
2022	J	`jnl`	Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models. Entropy Feng Xie, Yangbo He, Zhi Geng, Zhengming Chen, Ru Hou, Kun Zhang
2021	—	`conf`	Causal Discovery with Multi-Domain LiNGAM for Latent Factors. CAWS Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao
2021	A*	`conf`	Causal Discovery with Multi-Domain LiNGAM for Latent Factors. IJCAI Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao
2020	J	`jnl`	A causal discovery algorithm based on the prior selection of leaf nodes. Neural Networks Yan Zeng, Zhifeng Hao, Ruichu Cai, Feng Xie, Liang Ou, Ruihui Huang
2020	J	`jnl`	An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables. IEEE Trans. Neural Networks Learn. Syst. Feng Xie, Ruichu Cai, Yan Zeng, Jiantao Gao, Zhifeng Hao
2020	J	`jnl`	Causal Discovery with Multi-Domain LiNGAM for Latent Factors. CoRR Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao
2020	A*	`conf`	Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. NeurIPS Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
2020	J	`jnl`	Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs. CoRR Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
2020	J	`jnl`	Mining hidden non-redundant causal relationships in online social networks. Neural Comput. Appl. Wei Chen, Ruichu Cai, Zhifeng Hao, Chang Yuan, Feng Xie
2019	—	`conf`	Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples. IScIDE (2) Feng Xie, Ruichu Cai, Yan Zeng, Zhifeng Hao
2019	A*	`conf`	Triad Constraints for Learning Causal Structure of Latent Variables. NeurIPS Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang
2017	B	`conf`	An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data. IWQoS Ruichu Cai, Feng Xie, Wei Chen, Zhifeng Hao