James Theiler

24.4k total citations · 6 hit papers
220 papers, 12.6k citations indexed

About

James Theiler is a scholar working on Media Technology, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, James Theiler has authored 220 papers receiving a total of 12.6k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Media Technology, 61 papers in Artificial Intelligence and 52 papers in Aerospace Engineering. Recurrent topics in James Theiler's work include Remote-Sensing Image Classification (92 papers), Infrared Target Detection Methodologies (41 papers) and Geochemistry and Geologic Mapping (23 papers). James Theiler is often cited by papers focused on Remote-Sensing Image Classification (92 papers), Infrared Target Detection Methodologies (41 papers) and Geochemistry and Geologic Mapping (23 papers). James Theiler collaborates with scholars based in United States, Italy and United Kingdom. James Theiler's co-authors include Stephen Eubank, J. Doyne Farmer, André Longtin, B. Galdrikian, Simon Perkins, Dean Prichard, Bette Korber, Turab Lookman, Prasanna V. Balachandran and Dezhen Xue and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

James Theiler

211 papers receiving 12.0k citations

Hit Papers

Testing for nonlinearity ... 1986 2026 1999 2012 1992 1986 1990 2000 2016 500 1000 1.5k 2.0k 2.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
James Theiler 2.5k 2.3k 2.3k 1.8k 1.5k 220 12.6k
Kazuyuki Aihara 4.9k 2.0× 631 0.3× 3.5k 1.5× 4.8k 2.7× 4.0k 2.7× 815 17.5k
A. Arnéodo 2.6k 1.1× 2.8k 1.2× 299 0.1× 402 0.2× 3.5k 2.4× 228 10.7k
James A. Yorke 20.8k 8.3× 3.8k 1.7× 1.6k 0.7× 2.5k 1.4× 3.3k 2.3× 370 38.5k
Kenneth Lange 186 0.1× 295 0.1× 350 0.2× 1.8k 1.0× 5.1k 3.5× 274 23.2k
Alain Barrat 10.1k 4.0× 1.2k 0.5× 757 0.3× 1.2k 0.6× 1.3k 0.9× 170 17.3k
Stuart Geman 545 0.2× 756 0.3× 885 0.4× 5.9k 3.3× 813 0.6× 56 17.7k
Julian Besag 450 0.2× 3.2k 1.4× 174 0.1× 3.5k 2.0× 678 0.5× 60 16.1k
J. A. Tenreiro Machado 5.2k 2.1× 1.3k 0.6× 200 0.1× 1.6k 0.9× 533 0.4× 752 22.5k
Christian P. Robert 640 0.3× 1.2k 0.5× 367 0.2× 6.7k 3.7× 2.5k 1.7× 416 23.5k
Stephen Eubank 2.3k 0.9× 1.8k 0.8× 1.2k 0.5× 616 0.3× 566 0.4× 98 8.5k

Countries citing papers authored by James Theiler

Since Specialization
Citations

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

Fields of papers citing papers by James Theiler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Theiler

This figure shows the co-authorship network connecting the top 25 collaborators of James Theiler. A scholar is included among the top collaborators of James Theiler 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 James Theiler. James Theiler 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.
Beesley, Lauren J., Kelly R. Moran, Kshitij Wagh, et al.. (2023). SARS-CoV-2 variant transition dynamics are associated with vaccination rates, number of co-circulating variants, and convalescent immunity. EBioMedicine. 91. 104534–104534. 16 indexed citations
2.
Behnke, Sonja A., et al.. (2022). Discriminating Types of Volcanic Electrical Activity: Toward an Eruption Detection Algorithm. Geophysical Research Letters. 49(15). 1 indexed citations
3.
Shen, Xiaoying, Haili Tang, Charlene McDanal, et al.. (2021). SARS-CoV-2 variant B.1.1.7 is susceptible to neutralizing antibodies elicited by ancestral spike vaccines. Cell Host & Microbe. 29(4). 529–539.e3. 222 indexed citations breakdown →
4.
Love, Steven P., James Theiler, Bernard R. Foy, et al.. (2018). High-Resolution Hyperspectral Imaging of Dilute Gases from CubeSat Platforms. AGU Fall Meeting Abstracts. 2018. 3 indexed citations
5.
Lookman, Turab, et al.. (2016). Learning targeted materials properties from data. Bulletin of the American Physical Society. 2016. 1 indexed citations
6.
Balachandran, Prasanna V., Dezhen Xue, James Theiler, John Hogden, & Turab Lookman. (2016). Adaptive Strategies for Materials Design using Uncertainties. Scientific Reports. 6(1). 19660–19660. 164 indexed citations
7.
Theiler, James. (2011). Ellipsoid-simplex hybrid for hyperspectral anomaly detection. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 5806. 1–4. 12 indexed citations
8.
Scovel, Clint, Don Hush, Ingo Steinwart, & James Theiler. (2010). Radial kernels and their reproducing kernel Hilbert spaces. Journal of Complexity. 26(6). 641–660. 19 indexed citations
9.
Foy, Bernard R., James Theiler, & Andrew M. Fraser. (2009). Decision boundaries in two dimensions for target detection in hyperspectral imagery. Optics Express. 17(20). 17391–17391. 16 indexed citations
10.
Fischer, Will, Simon Perkins, James Theiler, et al.. (2006). Polyvalent vaccines for optimal coverage of potential T-cell epitopes in global HIV-1 variants. Nature Medicine. 13(1). 100–106. 325 indexed citations
11.
Perkins, Simon, et al.. (2003). Grafting: fast, incremental feature selection by gradient descent in function space. Journal of Machine Learning Research. 3. 1333–1356. 196 indexed citations
12.
Perkins, Simon & James Theiler. (2003). Online feature selection using grafting. International Conference on Machine Learning. 592–599. 138 indexed citations
13.
Kenyon, Garrett T., Bartlett D. Moore, Greg J. Stephens, et al.. (2003). A model of high-frequency oscillatory potentials in retinal ganglion cells. Visual Neuroscience. 20(5). 465–480. 25 indexed citations
14.
Woźniak, P. R., C. Akerlof, Susan Amrose, et al.. (2001). Classification of ROTSE Variable Stars using Machine Learning. AAS. 199. 1 indexed citations
15.
Harvey, Neal R., Steven P. Brumby, Simon Perkins, et al.. (2001). Image Feature Extraction: Genie vs Conventional Supervised Classification Techniques. PET Clinics. 12(1). 1–5. 11 indexed citations
16.
Leeser, Miriam & James Theiler. (2000). EFFECT OF DATA TRUNCATION IN AN IMPLEMENTATION OF PIXEL CLUSTERING ON A CUSTOM COMPUTING MACHINE. University of North Texas Digital Library (University of North Texas). 2 indexed citations
17.
Borel, Christoph C., William B. Clodius, Anthony B. Davis, et al.. (1999). MTI core science retrieval algorithms. 4 indexed citations
18.
Ho, Cheng, Kevin L. Albright, Jeffrey D. Bradley, et al.. (1999). Demonstration of literal three-dimensional imaging. Applied Optics. 38(9). 1833–1833. 18 indexed citations
19.
Theiler, James. (1994). Two tools to test time series data for evidence of chaos and/or nonlinearity. Integrative Psychological and Behavioral Science. 29(3). 211–216. 16 indexed citations
20.
Theiler, James, B. Galdrikian, André Longtin, Stephen Eubank, & J. Doyne Farmer. (1991). Using Surrogate Data to Detect Nonlinearity in Time Series. Physica A Statistical Mechanics and its Applications. 58. 77–94. 121 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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