Robust Density Estimation
Robust Density Estimation is a density estimation method that maintains accurate and stable performance in the presence of outliers, model misspecification, or deviations from underlying distributional assumptions, thereby distinguishing itself from conventional density estimation techniques by its resilience to data anomalies and modeling uncertainties.
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4.4K
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320
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2017–2026
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Robust and efficient estimation by minimising a density power divergence
Ayanendranath Basu · Biometrika · 1998 · 805 citations · Full text
Robust kernel density estimation
JooSeuk Kim, Clayton Scott · Journal of Machine Learning Research · 2012 · 183 citations
Robust Kernel Density Estimation
JooSeuk Kim, Clayton Scott · arXiv (Cornell University) · 2011 · 176 citations · Full text
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University of Michigan
Ann Arbor, United States
4 h-index
12 publications
616 citations
Stanford University
Stanford, United States
3 h-index
17 publications
251 citations

McGill University
Montreal, Canada
3 h-index
8 publications
109 citations

Newcastle University
Newcastle upon Tyne, United Kingdom
3 h-index
8 publications
184 citations

Shanghai Jiao Tong University
Shanghai, China
3 h-index
27 publications
1.1K citations
Michigan State University
East Lansing, United States
3 h-index
11 publications
175 citations
ShanghaiTech University
Shanghai, China
2 h-index
15 publications
420 citations

Indian Statistical Institute
Kolkata, India
2 h-index
3 publications
849 citations
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6 publications · 971 citations
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Repository · 5 publications · 273 citations
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5 publications · 363 citations
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4 publications · 187 citations
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JSCS · 4 publications · 71 citations
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