Data Smoothing
Data Smoothing is a data transformation technique that reduces random variation in a dataset by applying a mathematical function to approximate underlying patterns while attenuating noise.
507
Publications
38K
Citations
1.1K
Authors
523
Institutions
Publications per year
2017–2026
72
507
Smoothing noisy data with spline functions
Peter G. Craven, Grace Wahba · Numerische Mathematik · 1978 · 3.4K citations
Period determination using phase dispersion minimization
R. F. Stellingwerf · The Astrophysical Journal · 1978 · 1.5K citations
Natural Sciences, Astronomy, Physics +13
Smoothing noisy data with spline functions
Grace Wahba · Numerische Mathematik · 1975 · 1.5K citations
1–5 of 507
1.1K
6
h-index
University of North Carolina at Chapel Hill, United States
5 publications · 292 citations
5
h-index
5
h-index
4
h-index
4
h-index
1–5 of 1.1K
523
Stanford University
Stanford, United States
11 h-index
21 publications
3.3K citations
University of Washington
Seattle, United States
10 h-index
13 publications
594 citations
University of Wisconsin–Madison
Madison, United States
9 h-index
12 publications
4.4K citations

Commonwealth Scientific and Industrial Research Organisation
Canberra, Australia
8 h-index
13 publications
1.1K citations

University of Minnesota
Minneapolis, United States
7 h-index
8 publications
237 citations

University of British Columbia
Vancouver, Canada
5 h-index
14 publications
1K citations

Cornell University
Ithaca, United States
5 h-index
8 publications
434 citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
8 publications
539 citations
1–8 of 523
22 publications · 2K citations
19
h-index
CSDA · 9 publications · 1.2K citations
9
h-index
9 publications · 1.9K citations
9
h-index
TPAMI · 7 publications · 724 citations
7
h-index
6 publications · 5.4K citations
6
h-index
1–5