Giles Hooker

7.3k total citations · 3 hit papers
93 papers, 4.1k citations indexed

About

Giles Hooker is a scholar working on Artificial Intelligence, Statistics and Probability and Nature and Landscape Conservation. According to data from OpenAlex, Giles Hooker has authored 93 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 26 papers in Statistics and Probability and 11 papers in Nature and Landscape Conservation. Recurrent topics in Giles Hooker's work include Statistical Methods and Inference (21 papers), Explainable Artificial Intelligence (XAI) (10 papers) and Machine Learning and Data Classification (10 papers). Giles Hooker is often cited by papers focused on Statistical Methods and Inference (21 papers), Explainable Artificial Intelligence (XAI) (10 papers) and Machine Learning and Data Classification (10 papers). Giles Hooker collaborates with scholars based in United States, Canada and Australia. Giles Hooker's co-authors include J. O. Ramsay, Spencer Graves, Stephen P. Ellner, Peter B. Adler, Lucas Mentch, Rich Caruana, Michael R. Shirts, Eric Bair, Vijay S. Pande and David A. Campbell and has published in prestigious journals such as Physical Review Letters, Circulation and Ecology.

In The Last Decade

Giles Hooker

88 papers receiving 3.9k citations

Hit Papers

Functional Data Analysis with R and MATLAB 2007 2026 2013 2019 2009 2007 2021 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giles Hooker United States 28 871 574 533 469 418 93 4.1k
Michael Betancourt United States 11 855 1.0× 677 1.2× 927 1.7× 384 0.8× 519 1.2× 24 6.1k
Ben Goodrich United States 12 814 0.9× 672 1.2× 747 1.4× 338 0.7× 525 1.3× 26 5.7k
Jiqiang Guo United States 9 705 0.8× 551 1.0× 787 1.5× 341 0.7× 441 1.1× 13 5.2k
Bob Carpenter United States 14 1.2k 1.4× 519 0.9× 694 1.3× 451 1.0× 410 1.0× 28 5.7k
Allen Riddell United States 9 728 0.8× 517 0.9× 684 1.3× 316 0.7× 410 1.0× 22 4.9k
Daniel C. Lee Canada 11 710 0.8× 517 0.9× 684 1.3× 312 0.7× 410 1.0× 58 5.3k
Matthew D. Hoffman United States 17 2.6k 3.0× 527 0.9× 873 1.6× 430 0.9× 413 1.0× 54 7.9k
Jennifer A. Hoeting United States 22 813 0.9× 692 1.2× 1.1k 2.1× 275 0.6× 682 1.6× 54 5.2k
Christian Hennig United Kingdom 27 935 1.1× 293 0.5× 433 0.8× 265 0.6× 256 0.6× 73 3.0k
Peter Clifford United Kingdom 31 572 0.7× 509 0.9× 369 0.7× 295 0.6× 592 1.4× 109 4.7k

Countries citing papers authored by Giles Hooker

Since Specialization
Citations

This map shows the geographic impact of Giles Hooker'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 Giles Hooker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giles Hooker more than expected).

Fields of papers citing papers by Giles Hooker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giles Hooker. 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 Giles Hooker. The network helps show where Giles Hooker may publish in the future.

Co-authorship network of co-authors of Giles Hooker

This figure shows the co-authorship network connecting the top 25 collaborators of Giles Hooker. A scholar is included among the top collaborators of Giles Hooker based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Giles Hooker. Giles Hooker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xi, Xin, et al.. (2025). Pitfalls in machine learning interpretability: Manipulating partial dependence plots to hide discrimination. Insurance Mathematics and Economics. 125. 103135–103135.
2.
Warmenhoven, John, Franco M. Impellizzeri, Ian Shrier, et al.. (2025). Synthetic Data for Sharing and Exploration in High-Performance Sport: Considerations for Application. Sports Medicine. 55(8). 2019–2037.
3.
Zhou, Yunzhe, et al.. (2024). A generic approach for reproducible model distillation. Machine Learning. 113(10). 7645–7688. 1 indexed citations
4.
Hernández, Christina M., Stephen P. Ellner, Robin E. Snyder, & Giles Hooker. (2024). The natural history of luck: A synthesis study of structured population models. Ecology Letters. 27(3). e14390–e14390. 4 indexed citations
5.
Hernández, Christina M., Stephen P. Ellner, Peter B. Adler, Giles Hooker, & Robin E. Snyder. (2023). An exact version of Life Table Response Experiment analysis, and the R package exactLTRE. Methods in Ecology and Evolution. 14(3). 939–951. 8 indexed citations
6.
Mentch, Lucas, et al.. (2021). V-statistics and Variance Estimation. Journal of Machine Learning Research. 22(287). 1–48. 3 indexed citations
7.
Lengerich, Benjamin J., Sarah Tan, Chun‐Hao Chang, Giles Hooker, & Rich Caruana. (2020). Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models. International Conference on Artificial Intelligence and Statistics. 2402–2412. 3 indexed citations
8.
Wen, Jiaming, Philipp Köhler, Grégory Duveiller, et al.. (2020). A framework for harmonizing multiple satellite instruments to generate a long-term global high spatial-resolution solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment. 239. 111644–111644. 81 indexed citations
9.
Mentch, Lucas, et al.. (2019). Asymptotic Normality and Variance Estimation For Supervised Ensembles.. arXiv (Cornell University). 1 indexed citations
10.
Tredennick, Andrew T., et al.. (2018). Size‐by‐environment interactions: a neglected dimension of species' responses to environmental variation. Ecology Letters. 21(12). 1757–1770. 20 indexed citations
11.
Ellner, Stephen P., Robin E. Snyder, Peter B. Adler, & Giles Hooker. (2018). An expanded modern coexistence theory for empirical applications. Ecology Letters. 22(1). 3–18. 131 indexed citations
12.
Tan, Sarah, Rich Caruana, Giles Hooker, & Albert Gordo. (2018). Transparent Model Distillation.. arXiv (Cornell University). 6 indexed citations
13.
Tan, Sarah, Rich Caruana, Giles Hooker, & Yin Lou. (2017). Auditing Black-Box Models Using Transparent Model Distillation With Side Information. arXiv (Cornell University). 7 indexed citations
14.
Hooker, Giles & Lucas Mentch. (2016). Bootstrap bias corrections for ensemble methods. Statistics and Computing. 28(1). 77–86. 14 indexed citations
15.
Hall, Peter & Giles Hooker. (2015). Truncated Linear Models for Functional Data. Journal of the Royal Statistical Society Series B (Statistical Methodology). 78(3). 637–653. 29 indexed citations
16.
Hiltunen, Teppo, Nelson G. Hairston, Giles Hooker, Laura Jones, & Stephen P. Ellner. (2014). A newly discovered role of evolution in previously published consumer–resource dynamics. Ecology Letters. 17(8). 915–923. 74 indexed citations
17.
Mentch, Lucas & Giles Hooker. (2014). Ensemble Trees and CLTs: Statistical Inference for Supervised Learning. arXiv (Cornell University). 9 indexed citations
18.
Finkelman, Matthew, Giles Hooker, & Zhen Wang. (2010). Prevalence and Magnitude of Paradoxical Results in Multidimensional Item Response Theory. Journal of Educational and Behavioral Statistics. 35(6). 744–761. 7 indexed citations
19.
Hegland, Markus, Giles Hooker, & Stephen Roberts. (2009). Finite element thin plate splines in density estimation. ANZIAM Journal. 42. 712–712. 5 indexed citations
20.
Gelzer, Anna R., Marcus L. Koller, Niels F. Otani, et al.. (2008). Dynamic Mechanism for Initiation of Ventricular Fibrillation In Vivo. Circulation. 118(11). 1123–1129. 40 indexed citations

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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