| 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 | 109 | 2020 |
| 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 | 78 | 2019 |
| 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 | 61 | 2022 |
| 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 | 54 | 2022 |
| 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 | 29 | 2021 |
| 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 | 21 | 2022 |
| 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 | 19 | 2020 |
| 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 | 15 | 2023 |
| 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 | 14 | 2020 |
| 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 | 13 | 2021 |
| 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 | 10 | 2022 |
| 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 Journal of Machine Learning Research 25 (191), 1-61, 2024 | 8 | 2024 |
| 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 | 7 | 2023 |
| 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 | 7 | 2020 |
| 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 | 5 | 2017 |
| 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 | 4 | 2023 |
| 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 | 4 | 2023 |
| 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 | 4 | 2023 |
| Automating the Selection of Proxy Variables of Unmeasured Confounders F Xie, Z Chen, S Luo, W Miao, R Cai, Z Geng Forty-first International Conference on Machine Learning (ICML 2024), 2024 | 3 | 2024 |
| Local Causal Structure Learning in the Presence of Latent Variables F Xie, Z Li, P Wu, Y Zeng, C Liu, Z Geng Forty-first International Conference on Machine Learning (ICML 2024), 2024 | 3 | 2024 |
Ruichu CaiProfessor of Computer Science, Guangdong University of TechnologyE-mail megerősítve itt: gdut.edu.cn