Sparse Density Estimation
Sparse Density Estimation is a density estimation method that incorporates sparsity-inducing constraints or penalties to promote parsimonious models by selecting a minimal subset of components or features necessary to accurately represent the underlying probability distribution.
86
Publications
3.3K
Citations
220
Authors
131
Institutions
Publications per year
2017–2026
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University of Reading
Reading, United Kingdom
8 h-index
8 publications
200 citations
University of Southampton
Southampton, United Kingdom
8 h-index
14 publications
370 citations

Sorbonne Université
Paris, France
5 h-index
5 publications
156 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
9 publications
226 citations
University of Washington
Seattle, United States
3 h-index
3 publications
94 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
7 publications
398 citations

Data61
Sydney, Australia
3 h-index
4 publications
329 citations
Stanford University
Stanford, United States
3 h-index
5 publications
575 citations
1–8 of 131
Repository · 6 publications · 174 citations
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4 publications · 87 citations
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3 publications · 98 citations
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3 publications · 337 citations
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JCGS · 3 publications · 78 citations
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