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Feng Xie 0002
Person information
- affiliation: Peking University, School of Mathematical Sciences, Beijing, China
- affiliation: Guangdong University of Technology, School of Computer Science, Guangzhou, China
Other persons with the same name
- Feng Xie — disambiguation page
- Feng Xie 0001 — RMIT University, School of Computer Science and IT, Melbourne, Australia
- Feng Xie 0003
— National University of Defense Technology, Department of Computer Science, Changsha, China (and 1 more)
- Feng Xie 0004
- Feng Xie 0005 — China Information Technology Security Evaluation Center, Beijing, China
- Feng Xie 0006
- Feng Xie 0007 — McMaster University, Department of Computing and Software, Hamilton, Canada
- Feng Xie 0008 — Facebook Reality Labs, USA (and 1 more)
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2020 – today
- 2024
- [j7]Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang:
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. J. Mach. Learn. Res. 25: 191:1-191:61 (2024) - [c13]Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang:
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability. ICLR 2024 - [c12]Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng:
Automating the Selection of Proxy Variables of Unmeasured Confounders. ICML 2024 - [i7]Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng:
Automating the Selection of Proxy Variables of Unmeasured Confounders. CoRR abs/2405.16130 (2024) - [i6]Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang:
Learning Discrete Latent Variable Structures with Tensor Rank Conditions. CoRR abs/2406.07020 (2024) - 2023
- [j6]Feng Xie, Yan Zeng, Zhengming Chen
Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions. Neurocomputing 526: 48-61 (2023) - [j5]Yan Zeng
Nonlinear Causal Discovery for High-Dimensional Deterministic Data. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2234-2245 (2023) - [c11]Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai:
Some General Identification Results for Linear Latent Hierarchical Causal Structure. IJCAI 2023: 3568-3576 - [c10]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. NeurIPS 2023 - [i5]Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang:
Identification of Nonlinear Latent Hierarchical Models. CoRR abs/2306.07916 (2023) - [i4]Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang:
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR abs/2308.06718 (2023) - 2022
- [j4]Feng Xie
Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models. Entropy 24(4): 512 (2022) - [c9]Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai:
Identification of Linear Latent Variable Model with Arbitrary Distribution. AAAI 2022: 6350-6357 - [c8]Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang:
Identification of Linear Non-Gaussian Latent Hierarchical Structure. ICML 2022: 24370-24387 - [c7]Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang:
Latent Hierarchical Causal Structure Discovery with Rank Constraints. NeurIPS 2022 - [i3]Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang:
Latent Hierarchical Causal Structure Discovery with Rank Constraints. CoRR abs/2210.01798 (2022) - 2021
- [c6]Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao:
Causal Discovery with Multi-Domain LiNGAM for Latent Factors. CAWS 2021: 1-4 - [c5]Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao:
Causal Discovery with Multi-Domain LiNGAM for Latent Factors. IJCAI 2021: 2097-2103 - 2020
- [j3]Wei Chen, Ruichu Cai
Mining hidden non-redundant causal relationships in online social networks. Neural Comput. Appl. 32(11): 6913-6923 (2020) - [j2]Yan Zeng
A causal discovery algorithm based on the prior selection of leaf nodes. Neural Networks 124: 130-145 (2020) - [j1]Feng Xie
An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables. IEEE Trans. Neural Networks Learn. Syst. 31(5): 1667-1680 (2020) - [c4]Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang:
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. NeurIPS 2020 - [i2]Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao:
Causal Discovery with Multi-Domain LiNGAM for Latent Factors. CoRR abs/2009.09176 (2020) - [i1]Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang:
Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs. CoRR abs/2010.04917 (2020)
2010 – 2019
- 2019
- [c3]Feng Xie
Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples. IScIDE (2) 2019: 381-393 - [c2]Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang:
Triad Constraints for Learning Causal Structure of Latent Variables. NeurIPS 2019: 12863-12872 - 2017
- [c1]Ruichu Cai, Feng Xie
An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data. IWQoS 2017: 1-6
Coauthor Index
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