Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process

Author:

Wu Ben1,Guo Ying2,Kang Jian3ORCID

Affiliation:

1. Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China

2. Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA

3. Department of Biostatistics, University of Michigan, Ann Arbor, MI

Funder

National Institute of General Medical Sciences

National Institute of Mental Health

National Institute on Drug Abuse

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A review on the application of blind source separation in vibration analysis of mechanical systems;Measurement;2024-03

2. Latent subgroup identification in image-on-scalar regression;The Annals of Applied Statistics;2024-03-01

3. Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics;2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT);2024-02-19

4. BSPBSS: Bayesian Spatial Blind Source Separation;CRAN: Contributed Packages;2022-09-02

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