Infinite Mixture Models
Infinite Mixture Models is a Bayesian nonparametric model that extends finite mixture models by allowing a countably infinite number of components, thereby enabling flexible and data-driven inference of cluster structure without pre-specifying the number of clusters.
241
Publications
13.5K
Citations
549
Authors
307
Institutions
Publications per year
2017–2026
58
Variants
Infinite Mixture Model
241
The Infinite Gaussian Mixture Model
Carl Edward Rasmussen · 1999 · 992 citations
Bayesian hierarchical clustering
Katherine Heller, Zoubin Ghahramani · 2005 · 371 citations
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Concordia University
Montreal, Canada
14 h-index
24 publications
805 citations
University of Kent
Canterbury, United Kingdom
6 h-index
9 publications
526 citations
Taif University
Ta'if, Saudi Arabia
5 h-index
9 publications
231 citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
10 publications
398 citations
Indiana University – Purdue University Indianapolis
Indianapolis, United States
4 h-index
7 publications
179 citations
Huaqiao University
Xiamen, China
4 h-index
4 publications
75 citations
University of California, Berkeley
Berkeley, United States
4 h-index
5 publications
576 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
7 publications
197 citations
1–8 of 307
Repository · 12 publications · 533 citations
11
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CSDA · 8 publications · 369 citations
8
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6 publications · 466 citations
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6 publications · 124 citations
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5 publications · 285 citations
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