Robust Data Preprocessing
Robust Data Preprocessing is a data preparation methodology that belongs to the class of outlier treatment techniques and is distinguished by its capacity to minimize the influence of outliers and noise on downstream analysis through stable, outlier-resistant transformations without prior assumptions about the underlying data distribution.
125
Publications
18.5K
Citations
448
Authors
236
Institutions
Publications per year
2017–2026
53
Parents
125
fMRIPrep: a robust preprocessing pipeline for functional MRI
Oscar Estéban, Christopher J. Markiewicz, Ross Blair et al. · Nature Methods · 2018 · 4.2K citations
Methods for dealing with reaction time outliers.
Roger Ratcliff · Psychological Bulletin · 1993 · 2.1K citations
Outlier Treatment in Data Merging
R. H. Blessing · Journal of Applied Crystallography · 1997 · 1.3K citations
Computing, Mathematics, Data Mining +16
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236
KU Leuven
Leuven, Belgium
5 h-index
10 publications
470 citations

Vanderbilt University
Nashville, United States
3 h-index
8 publications
152 citations
Stanford University
Stanford, United States
3 h-index
19 publications
39.8K citations

Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
2 h-index
3 publications
118 citations

Sapienza University of Rome
Rome, Italy
2 h-index
4 publications
392 citations
University of Iowa
Iowa City, United States
2 h-index
2 publications
4.4K citations
Vrije Universiteit Brussel
Brussels, Belgium
2 h-index
6 publications
274 citations
The University of Texas at Austin
Austin, United States
2 h-index
2 publications
163 citations
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3 publications · 324 citations
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CSDA · 3 publications · 316 citations
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2 publications · 317 citations
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2 publications · 242 citations
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2 publications · 2.3K citations
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