Bayesian Nonparametric Models: Applications and Extensions in Complex Data Modeling
Abstract
biomedicine, and artificial intelligence poses severe challenges to the preset structures and fixed-dimensional assumptions of traditional
parametric models. Bayesian nonparametric models, leveraging their core advantages of “adaptive parameter dimensionality,” “strong prior
flexibility,” and “accurate uncertainty quantification,” have become a key tool for complex data modeling.
Keywords
Full Text:
PDFReferences
[1]Li Shuaipeng Application of Bayesian prediction analysis decision system in third-party detection of operational risks in engineering
[J]. Journal of Natural Sciences, Harbin Normal University, 2025, 41 (03): 18-22
[2]Xiao Shuyu, Fang Zhigeng, Du Yangyang, etc Bayesian Prior Information Hybrid Regeneration Grey Entropy Weight Model [J/
OL]. Chinese Management Science, 1-12 [2021-11-13] https://doi.org/10.16381/j.cnki.issn1003-207x.2023.1244.
[3]Xia Juan Construction and Application Research of Bayesian Change Point Detection Model [D]. Huazhong Agricultural University, 2023. DOI: 10.27158/d.cnki.ghznu.2023.001874
[4]Peng Minjiao Research on Tax Compliance Issues in the Digital Economy [D]. Yunnan University of Finance and Economics, 2023.
DOI: 10.27455/d.cnki.gycmc.2023.001170
[5]Zhang Mengli Research on the Construction and Practice of Human Computer Collaborative Teaching Mode in the Era of Artificial
Intelligence [D]. Zhejiang Normal University, 2023. DOI: 10.27464/d.cnki.gzsfu.2023.001583
DOI: http://dx.doi.org/10.18686/fm.v10i6.14342
Refbacks
- There are currently no refbacks.
