Gaussian Sequence Models
Gaussian Sequence Models is a statistical framework within empirical Bayes methodology that characterizes observations as noisy realizations of an unknown sequence of parameters, distinguished by the assumption that both the noise and the prior distribution of parameters follow Gaussian distributions.
30
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1.9K
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52
Authors
34
Institutions
Publications per year
2017–2026
8
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Gaussian Sequence Model
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Southwest University
Chongqing, China
3 h-index
4 publications
67 citations
University of New Orleans
New Orleans, United States
2 h-index
4 publications
58 citations
Université Paris-Sud
Orsay, France
2 h-index
3 publications
2.2K citations
University of Minnesota, Duluth
Duluth, United States
2 h-index
4 publications
93 citations
Stanford University
Stanford, United States
2 h-index
2 publications
66 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
3 publications
87 citations

Sorbonne Université
Paris, France
2 h-index
2 publications
64 citations
Centre de Recherche en Mathématiques de la Décision
Paris, France
1 h-index
1 publications
66 citations
1–8 of 34
8 publications · 1.3K citations
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2 publications · 49 citations
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2 publications · 29 citations
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2 publications · 36 citations
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1 publications · 15 citations
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