Adaptive Basis Selection
Adaptive Basis Selection is a method within the framework of Polynomial Chaos Expansions that systematically identifies and retains the most influential polynomial basis functions based on sensitivity measures or error indicators to improve approximation accuracy and computational efficiency.
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2017–2026
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CART and best-ortho-basis: a connection
David L. Donoho · The Annals of Statistics · 1997 · 214 citations · Full text
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University of California, Berkeley
Berkeley, United States
7 h-index
11 publications
3.4K citations
Yale University
New Haven, United States
4 h-index
7 publications
610 citations
University of Southern California
Los Angeles, United States
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7 publications
329 citations
ETH Zurich
Zurich, Switzerland
4 h-index
7 publications
386 citations

Lawrence Berkeley National Laboratory
Berkeley, United States
4 h-index
13 publications
614 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
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4 publications
1K citations

University of Electronic Science and Technology of China
Chengdu, China
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9 publications
320 citations

Lawrence Livermore National Laboratory
Livermore, United States
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3 publications
106 citations
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