Kernel-based Mixture Modeling
Kernel-Based Mixture Modeling is a statistical framework within mixture dose-response modeling that employs kernel functions to nonparametrically represent component distributions, thereby enabling flexible estimation of complex response patterns arising from heterogeneous subpopulations.
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2.2K
Citations
101
Authors
73
Institutions
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2017–2026
8
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A mixture model for representing shape variation
T.F. Cootes, Chris Taylor · Image and Vision Computing · 1999 · 254 citations
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73

Indian Institute of Science Bangalore
Bengaluru, India
2 h-index
2 publications
97 citations

Concordia University
Montreal, Canada
2 h-index
3 publications
200 citations

Australian National University
Canberra, Australia
2 h-index
4 publications
88 citations

Data61
Sydney, Australia
2 h-index
4 publications
55 citations
University of Michigan
Ann Arbor, United States
2 h-index
4 publications
194 citations

University of Ioannina
Ioannina, Greece
2 h-index
3 publications
50 citations
KU Leuven
Leuven, Belgium
2 h-index
2 publications
42 citations

University of Manchester
Manchester, United Kingdom
2 h-index
4 publications
572 citations
1–8 of 73
2 publications · 309 citations
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TKDE · 1 publications · 88 citations
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JSS · 1 publications · 40 citations
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1 publications · 254 citations
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1 publications · 57 citations
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