Feng Xie
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个人简介
现任北京工商大学应用统计系副教授。在加入BTBU之前，于2020年至2022年在北京大学概率与统计系从事博士后研究，合作导师是耿直教授和何洋波教授 。于2017 - 2020年在广东工业大学计算机学院获得博士学位，师从 蔡瑞初教授 和 Kun Zhang （卡内基·梅隆大学）。于2014-2017年在广东工业大学数学与统计学院获得硕士学位，师从郝志峰教授。 于2019-2020年以访问学生身份到美国卡内基梅隆大学学习。
研究兴趣:
因果推断、机器学习、因果网络、贝叶斯网络、因果因子分析
目前正在招募2023级研究生. 欢迎有兴趣的同学联系我!
Selected Publications (* Equal Contribution)
Latent Causal Structure/Causal Factor Analysis/Causal Representation LearningFeng Xie, Yan Zeng, Zhengming Chen, Yangbo He, Zhi Geng, and Kun Zhang. Causal Discovery of 1-Factor Measurement Models in Linear Latent Variable Models with Arbitrary Noise Distributions. Neurocomputing, 2023.
Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, and Kun Zhang. Identification of Linear Non-Gaussian Latent Hierarchical Structure. Thirty-ninth International Conference on Machine Learning (ICML), Baltimore, Maryland USA, 2022. [pdf][code]
Feng Xie*, Ruichu Cai*, Biwei Huang, Clark Glymour, Zhifeng Hao, and Kun Zhang*. Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. Advances in Neural Information Processing Systems 33 (NeurIPS), Virtual Conference, 2020. [pdf][Matlab code][Python code] (Spotlight)
Feng Xie, Ruichu Cai, Yan Zeng, and Zhifeng Hao. An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models with IID Noise Variables. IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2020, 31(5): 1667-1680. (JCR Q1, IF 11.683)
Ruichu Cai*, Feng Xie*, Clark Glymour, Zhifeng Hao, and Kun Zhang. Triad Constraints for Causal Discovery in the Presence of Latent Variables. Advances in Neural Information Processing Systems 32 (NeurIPS), Vancouver, CANADA, 2019. [pdf] [code]
Z. Chen*, Feng Xie*, Jie Qiao*, Zhifeng Hao, Kun Zhang, and Ruichu Cai. Identification of Linear Latent Variable Model with Arbitrary Distribution. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Vancouver, CANADA, 2022. [pdf]
Biwei Huang*, Charles Low*, Feng Xie, Clark Glymour, Kun Zhang. Latent Hierarchical Causal Structure Discovery with Rank Constraints. Advances in Neural Information Processing Systems (NeurIPS), 2022
Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, and Zhifeng Hao. Causal discovery with multi-domain LiNGAM for latent factors. Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), Montreal-themed Virtual Reality, 2021.
Feng Xie, Yangbo He, Zhi Geng, Zhengming Chen, Ru Hou, and Kun Zhang. Testability of Instrument Validity in Linear non-Gaussian Acyclic Causal Models. Entropy, 2022, 24(4), 512. [pdf](JCR Q2, IF 2.524)