( en | de | ru )

 

Disambiguation of "Shimizu, Shohei"

Author of the publication

copydeleteadd this publication to your clipboard
Testing Significance of Mixing and Demixing Coefficients in ICA.

, , , , and . ICA, volume 3889 of Lecture Notes in Computer Science, page 901-908. Springer, (2006)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Takayasu Shimizu

Kenichi Shimizu

Toshiyoshi Shimizu

Akiko Shimizu

Masumi Shimizu

 

Other publications of authors with the same name

Python package for causal discovery based on LiNGAM., , , , and . J. Mach. Learn. Res., (2023)Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems., , , , , , and . IEEE Trans. Ind. Informatics, 18 (2): 1377-1386 (2022)GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables, , , and . CoRR, (2010)Estimation of linear non-Gaussian acyclic models for latent factors., , and . Neurocomputing, 72 (7-9): 2024-2027 (2009)Learning Instrumental Variables with Structural and Non-Gaussianity Assumptions., and . J. Mach. Learn. Res., (2017)A Linear Non-Gaussian Acyclic Model for Causal Discovery., , , and . J. Mach. Learn. Res., (2006)Discovery of Exogenous Variables in Data with More Variables Than Observations., , , , , and . ICANN (1), volume 6352 of Lecture Notes in Computer Science, page 67-76. Springer, (2010)Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating., , and . CoRR, (2024)Estimating individual-level optimal causal interventions combining causal models and machine learning models., , , , , and . CD@KDD, volume 150 of Proceedings of Machine Learning Research, page 55-77. PMLR, (2021)Nonlinear Causal Discovery for High-Dimensional Deterministic Data., , , , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (5): 2234-2245 (May 2023)