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Feng Xie
Feng Xie
Associate Professor, Beijing Technology and Business University
Verified email at btbu.edu.cn - Homepage
Title
Cited by
Cited by
Year
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
F Xie, R Cai, B Huang, C Glymour, Z Hao, K Zhang
Advances in Neural Information Processing Systems 34 (NeurIPS 2020), 2020
762020
Triad constraints for learning causal structure of latent variables
R Cai, F Xie, C Glymour, Z Hao, K Zhang
Advances in Neural Information Processing Systems 33 (NeurIPS 2019), 2019
582019
Identification of Linear Non-Gaussian Latent Hierarchical Structure
F Xie, B Huang, Z Chen, Y He, Z Geng, K Zhang
International Conference on Machine Learning (ICML 2022), 24370-24387, 2022
382022
Latent hierarchical causal structure discovery with rank constraints
B Huang, CJH Low, F Xie, C Glymour, K Zhang
Advances in Neural Information Processing Systems 36 (NeurIPS 2022), 2022
292022
Causal discovery with multi-domain LiNGAM for latent factors
Y Zeng, S Shimizu, R Cai, F Xie, M Yamamoto, Z Hao
The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), 2021
182021
An efficient entropy-based causal discovery method for linear structural equation models with IID noise variables
F Xie, R Cai, Y Zeng, J Gao, Z Hao
IEEE Transactions on Neural Networks and Learning Systems 31 (5), 1667-1680, 2020
162020
Identification of Linear Latent Variable Model with Arbitrary Distribution
Z Chen, F Xie, J Qiao, Z Hao, K Zhang, R Cai
Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), 2022
112022
Mining hidden non-redundant causal relationships in online social networks
W Chen, R Cai, Z Hao, C Yuan, F Xie
Neural Computing and Applications 32, 6913-6923, 2020
112020
Nonlinear causal discovery for high-dimensional deterministic data
Y Zeng, Z Hao, R Cai, F Xie, L Huang, S Shimizu
IEEE Transactions on Neural Networks and Learning Systems 34 (5), 2234-2245, 2021
82021
Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions
F Xie, Y Zeng, Z Chen, Y He, Z Geng, K Zhang
Neurocomputing 526, 48-61, 2023
52023
A causal discovery algorithm based on the prior selection of leaf nodes
Y Zeng, Z Hao, R Cai, F Xie, L Ou, R Huang
Neural Networks 124, 130-145, 2020
52020
An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data
R Cai, F Xie, W Chen, Z Hao
2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS 2017), 2017
52017
Identification of Nonlinear Latent Hierarchical Models
L Kong, B Huang, F Xie, E Xing, Y Chi, K Zhang
Advances in Neural Information Processing Systems 37 (NeurIPS 2023), 2023
42023
Generalized independent noise condition for estimating causal structure with latent variables
F Xie, B Huang, Z Chen, R Cai, C Glymour, Z Geng, K Zhang
arXiv preprint arXiv:2308.06718, 2023
32023
Testability of instrumental variables in linear non-Gaussian acyclic causal models
F Xie, Y He, Z Geng, Z Chen, R Hou, K Zhang
Entropy 24 (4), 512, 2022
32022
Identification and estimation of causal effects using non-gaussianity and auxiliary covariates
K Shuai, S Luo, Y Zhang, F Xie, Y He
arXiv preprint arXiv:2304.14895, 2023
22023
Some General Identification Results for Linear Latent Hierarchical Causal Structure
Z Chen, F Xie, J Qiao, Z Hao, R Cai
International Joint Conference on Artificial Intelligence (IJCAI 2023), 2023
22023
Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples
F Xie, R Cai, Y Zeng, Z Hao
International Conference on Intelligent Science and Big Data Engineering …, 2019
12019
Testing Conditional Independence Between Latent Variables by Independence Residuals
Z Chen, J Qiao, F Xie, R Cai, Z Hao, K Zhang
IEEE Transactions on Neural Networks and Learning Systems, 2024
2024
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
S Jin, F Xie, G Chen, B Huang, Z Chen, X Dong, K Zhang
The Twelfth International Conference on Learning Representations (ICLR 2024), 2023
2023
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