Feng Xie

Orcid: 0000-0001-7229-3955

Affiliations:
  • Peking University, School of Mathematical Sciences, Beijing, China
  • Guangdong University of Technology, School of Computer Science, Guangzhou, China


According to our database1, Feng Xie authored at least 18 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Nonlinear Causal Discovery for High-Dimensional Deterministic Data.
IEEE Trans. Neural Networks Learn. Syst., May, 2023

Causal discovery of 1-factor measurement models in linear latent variable models with arbitrary noise distributions.
Neurocomputing, March, 2023

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables.
CoRR, 2023

Identification of Nonlinear Latent Hierarchical Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Some General Identification Results for Linear Latent Hierarchical Causal Structure.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
Testability of Instrumental Variables in Linear Non-Gaussian Acyclic Causal Models.
Entropy, 2022

Latent Hierarchical Causal Structure Discovery with Rank Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Identification of Linear Non-Gaussian Latent Hierarchical Structure.
Proceedings of the International Conference on Machine Learning, 2022

Identification of Linear Latent Variable Model with Arbitrary Distribution.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Causal Discovery with Multi-Domain LiNGAM for Latent Factors.
Proceedings of the Causal Analysis Workshop Series, 2021

2020
An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models With IID Noise Variables.
IEEE Trans. Neural Networks Learn. Syst., 2020

A causal discovery algorithm based on the prior selection of leaf nodes.
Neural Networks, 2020

Mining hidden non-redundant causal relationships in online social networks.
Neural Comput. Appl., 2020

Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs.
CoRR, 2020

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Triad Constraints for Learning Causal Structure of Latent Variables.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Causal Discovery of Linear Non-Gaussian Acyclic Model with Small Samples.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 2019

2017
An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data.
Proceedings of the 25th IEEE/ACM International Symposium on Quality of Service, 2017


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