Probabilistic Clustering
Probabilistic Clustering is a clustering methodology that models cell-to-cluster assignments through probability distributions, distinguishing itself by quantifying uncertainty in cluster membership via statistical inference rather than enforcing hard or deterministic partitions.
350
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22K
Citations
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475
Institutions
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2017–2026
84
Parents
350
Arindam Bhattacharjee, William G. Richards, Jane Staunton et al. · Proceedings of the National Academy of Sciences · 2001 · 2.6K citations · Full text
Absalom E. Ezugwu, Abiodun M. Ikotun, Olaide O. Oyelade et al. · Engineering Applications of Artificial Intelligence · 2022 · 882 citations
A Mixture Model for Clustering Ensembles
A. Topchy, Anil K. Jain, William F. Punch · 2004 · 385 citations
Computing, Data Science, Data Mining +15
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Centre National de la Recherche Scientifique
Paris, France
8 h-index
16 publications
1.3K citations
University of Missouri
Columbia, United States
7 h-index
14 publications
1.5K citations
University of California, Irvine
Irvine, United States
6 h-index
13 publications
1.5K citations

Shenzhen University
Shenzhen, China
5 h-index
9 publications
220 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
5 h-index
16 publications
1.7K citations
Stanford University
Stanford, United States
5 h-index
11 publications
440 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
5 h-index
9 publications
417 citations

University of Milano-Bicocca
Milan, Italy
4 h-index
8 publications
267 citations
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8 publications · 336 citations
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TFS · 8 publications · 563 citations
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7 publications · 429 citations
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7 publications · 358 citations
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TPAMI · 7 publications · 402 citations
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