High-dimensional Density Estimation
High-Dimensional Density Estimation is a statistical methodology concerned with inferring the probability density function of a random variable in high-dimensional spaces, where the challenge arises from the curse of dimensionality rendering traditional estimation techniques inefficient or infeasible.
138
Publications
12.9K
Citations
304
Authors
156
Institutions
Publications per year
2017–2026
38
Parents
138
Automatic Choice of Dimensionality for PCA
Thomas P. Minka · 2000 · 473 citations
Improved fast gauss transform and efficient kernel density estimation
Yang, Duraiswami, Gumerov et al. · 2003 · 404 citations
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156
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
15 publications
4K citations
Georgia Institute of Technology
Atlanta, United States
6 h-index
8 publications
219 citations
Stanford University
Stanford, United States
5 h-index
12 publications
623 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
16 publications
783 citations
Institut d'Astrophysique de Paris
Paris, France
4 h-index
9 publications
208 citations
University of California, Berkeley
Berkeley, United States
3 h-index
4 publications
360 citations
Courant Institute of Mathematical Sciences
New York, United States
3 h-index
4 publications
464 citations
Tokyo Institute of Technology
Tokyo, Japan
3 h-index
6 publications
820 citations
1–8 of 156
Repository · 23 publications · 1.1K citations
15
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11 publications · 623 citations
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TPAMI · 4 publications · 1.6K citations
4
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3 publications · 73 citations
3
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Conference · 3 publications · 105 citations
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