Symbolic Regression
Symbolic Regression is a regression method that, unlike conventional parametric approaches, automatically discovers the mathematical expression and functional form of a model by searching through symbolic representations of relationships among variables using evolutionary computation techniques.
618
Publications
25.6K
Citations
1.5K
Authors
610
Institutions
Publications per year
2017–2026
384
618
1–5 of 618
1.5K
18
h-index
17
h-index
14
h-index
University of Applied Sciences Upper Austria, Austria
13 publications · 487 citations
12
h-index
University of Applied Sciences Upper Austria, Austria
11 publications · 574 citations
11
h-index
1–5 of 1.5K
610

Victoria University of Wellington
Wellington, New Zealand
19 h-index
88 publications
3.5K citations
University of Applied Sciences Upper Austria
Wels, Austria
13 h-index
45 publications
2K citations

Delft University of Technology
Delft, The Netherlands
12 h-index
17 publications
557 citations

Centre National de la Recherche Scientifique
Paris, France
11 h-index
21 publications
704 citations

Cornell University
Ithaca, United States
11 h-index
20 publications
910 citations

Poznań University of Technology
Poznan, Poland
10 h-index
26 publications
992 citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
31 publications
799 citations

Johannes Kepler University of Linz
Linz, Austria
9 h-index
22 publications
837 citations
1–8 of 610
19 publications · 1.8K citations
17
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Repository · 26 publications · 1.1K citations
16
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Conference · 9 publications · 234 citations
10
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9 publications · 884 citations
9
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6 publications · 200 citations
9
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