Sparse Bayesian Models
Sparse Bayesian Models is a Bayesian modeling framework that belongs to the class of probabilistic models characterized by the incorporation of prior distributions promoting sparsity, distinguishing it through its explicit mechanism for driving irrelevant or weakly supported parameters toward zero in order to achieve parsimonious representations.
576
Publications
31.7K
Citations
1.6K
Authors
608
Institutions
Publications per year
2017–2026
310
Parents
576
Sparse Bayesian Learning for Basis Selection
David Wipf, Bhaskar D. Rao · IEEE Transactions on Signal Processing · 2004 · 1.5K citations
Fast Marginal Likelihood Maximisation for Sparse Bayesian Models
Michael E. Tipping, Anita Faul · 2003 · 726 citations
1–5 of 576
1.6K
15
h-index
14
h-index
14
h-index
12
h-index
10
h-index
1–5 of 1.6K
608
University of California San Diego
San Diego, United States
30 h-index
90 publications
10.7K citations

University of Electronic Science and Technology of China
Chengdu, China
15 h-index
45 publications
1.4K citations
Jiangsu University
Zhenjiang, China
14 h-index
25 publications
1.6K citations

Zhejiang University
Hangzhou, China
14 h-index
25 publications
1.3K citations

Harbin Institute of Technology
Harbin, China
12 h-index
31 publications
989 citations

Scripps Institution of Oceanography
La Jolla, United States
12 h-index
32 publications
1.6K citations

Chinese Academy of Sciences
Beijing, China
12 h-index
54 publications
1.6K citations
Duke University
Durham, United States
12 h-index
34 publications
1.6K citations
1–8 of 608
36 publications · 4K citations
26
h-index
15 publications · 380 citations
14
h-index
18 publications · 677 citations
14
h-index
13 publications · 955 citations
13
h-index
Repository · 15 publications · 1.6K citations
12
h-index
1–5