Grace Wahba

32.7k citations
148 papers · 21.9k indexed · 11 hit papers · h-index 46

Impact in

Papers in

Grace Wahba

144 papers receiving 19.9k citations

Hit Papers

Multicategory Support Vector Machines 2004 · 477 citations
477196520261985200510002.0k3.0k

Peers

Grace Wahba
Comparison fields: 5 of 217
  • Statistics and Probability 5.5k
  • Applied Mathematics 2.1k
  • Statistics, Probability and Uncertainty 1.4k
  • Mathematical Physics 1.6k
  • Computer Vision and Pattern Recognition 3.6k
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Citations per field
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Citations per year

Countries citing papers authored by Grace Wahba

Since Specialization
Citations

This map shows the geographic impact of Grace Wahba's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Grace Wahba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grace Wahba more than expected).

Fields of papers citing papers by Grace Wahba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grace Wahba. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Grace Wahba. The network helps show where Grace Wahba may publish in the future.

Co-authors

The 25 scholars most cited alongside Grace Wahba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Grace Wahba Line = papers co-authored together Grace Wahba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201225
2
Learning Higher-Order Graph Structure with Features by Structure Penalty
20119
3
The Bias-Variance Tradeoff and the Randomized GACV
199828
4
Backfitting in smoothing spline anova, with application to historical global temperature data
19963
5 19955
6
Structured Machine Learning for 'Soft' Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing and Evaluation
199315
7 199368
8 199043
9
Cross spectral distribution theory for mixed spectra and estimation of prediction filter coefficients
19872
10 198760
11
Design criteria and eigensequence plots for satellite computed tomography
19831
12
Cross Validated Spline Methods for Direct and Indirect Sensing Experiments.
19821
13 19819
14
Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
Hit paper breakdown →
19792651
15
Design Problems for Optimal Surface Interpolation.
197917
16
Smoothing noisy data with spline functions
Hit paper breakdown →
19782456
17 197617
18
A Canonical Form For the Problem of Estimating Smooth Surfaces.
19752
19 197439
20 197344

About Grace Wahba

Grace Wahba is a scholar working on Statistics and Probability, Computational Mathematics, Applied Mathematics, Mathematical Physics and Numerical Analysis, having authored 148 papers that have together received 21.9k indexed citations. Recurring topics across this work include Statistical Methods and Inference (30 papers), Statistical and numerical algorithms (18 papers), Numerical methods in inverse problems (16 papers), Advanced Statistical Methods and Models (15 papers), Advanced Numerical Analysis Techniques (12 papers), Mathematical functions and polynomials (12 papers), Matrix Theory and Algorithms (11 papers) and Statistical Methods and Bayesian Inference (11 papers). The work is most often cited by research in Statistics and Probability (5.5k citations), Applied Mathematics (2.1k citations), Statistics, Probability and Uncertainty (1.4k citations), Mathematical Physics (1.6k citations) and Computer Vision and Pattern Recognition (3.6k citations). Grace Wahba has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Hans‐Georg Müller, Peter G. Craven, Michael T. Heath, Gene H. Golub, George Kimeldorf, Yi Lin, Yoonkyung Lee, Chong Gu, James Wendelberger and Svante Wold. Their work appears in journals such as Journal of the American Statistical Association, The Annals of Statistics, Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of Approximation Theory and Proceedings of the National Academy of Sciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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