Ian T. Nabney

1.6k total citations · 1 hit paper
56 papers, 1.1k citations indexed

About

Ian T. Nabney is a scholar working on Artificial Intelligence, Molecular Biology and Control and Systems Engineering. According to data from OpenAlex, Ian T. Nabney has authored 56 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 10 papers in Molecular Biology and 9 papers in Control and Systems Engineering. Recurrent topics in Ian T. Nabney's work include Neural Networks and Applications (11 papers), Fault Detection and Control Systems (7 papers) and Ocean Waves and Remote Sensing (7 papers). Ian T. Nabney is often cited by papers focused on Neural Networks and Applications (11 papers), Fault Detection and Control Systems (7 papers) and Ocean Waves and Remote Sensing (7 papers). Ian T. Nabney collaborates with scholars based in United Kingdom, United States and Spain. Ian T. Nabney's co-authors include Niya Chen, Zheng Qian, Xiaofeng Meng, Peter Tiňo, Dan Cornford, John R. Owen, Fabián López-Vallejo, José L. Medina‐Franco, Andreas Sewing and Christopher K. I. Williams and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Ian T. Nabney

54 papers receiving 1.0k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Wind Power Forecasts Using Gaussian Processes and Numerical Weather Prediction

2013 345 citations Niya Chen, Zheng Qian et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ian T. Nabney United Kingdom	14	428	304	152	118	108	56	1.1k
Margaret E. Lundy Canada	11	118 0.3×	261 0.9×	96 0.6×	156 1.3×	64 0.6×	13	1.3k
Qi Sun China	22	304 0.7×	283 0.9×	41 0.3×	32 0.3×	280 2.6×	131	1.3k
Mark A. Kramer United States	19	105 0.2×	546 1.8×	156 1.0×	73 0.6×	75 0.7×	41	1.9k
Anindya Roy United States	17	52 0.1×	219 0.7×	86 0.6×	39 0.3×	61 0.6×	73	1.1k
Babak E. Cohanim United States	9	232 0.5×	205 0.7×	21 0.1×	99 0.8×	118 1.1×	29	1.1k
Dan Yamins United States	2	128 0.3×	393 1.3×	98 0.6×	108 0.9×	123 1.1×	3	1.1k
Ian Nabney United Kingdom	7	73 0.2×	285 0.9×	78 0.5×	51 0.4×	162 1.5×	20	860
Jan Kloppenborg Møller Denmark	22	692 1.6×	268 0.9×	77 0.5×	8 0.1×	29 0.3×	79	1.4k

Countries citing papers authored by Ian T. Nabney

Since Specialization

Citations

This map shows the geographic impact of Ian T. Nabney'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 Ian T. Nabney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian T. Nabney more than expected).

Fields of papers citing papers by Ian T. Nabney

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian T. Nabney. 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 Ian T. Nabney. The network helps show where Ian T. Nabney may publish in the future.

Co-authorship network of co-authors of Ian T. Nabney

This figure shows the co-authorship network connecting the top 25 collaborators of Ian T. Nabney. A scholar is included among the top collaborators of Ian T. Nabney 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 Ian T. Nabney. Ian T. Nabney is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Mumtaz, Shahzad, Ian T. Nabney, & Darren R. Flower. (2017). Scrutinizing human MHC polymorphism: Supertype analysis using Poisson-Boltzmann electrostatics and clustering. Journal of Molecular Graphics and Modelling. 77. 130–136. 3 indexed citations

Nabney, Ian T., et al.. (2016). Early warnings of heart rate deterioration. PubMed. 101. 940–943. 2 indexed citations

Nabney, Ian T., et al.. (2015). Bagging model with cost sensitive analysis on diabetes data. Aston Publications Explorer (Aston University). 11(1). 82–90. 1 indexed citations

Chen, Niya, Zheng Qian, Xiaofeng Meng, & Ian T. Nabney. (2013). Short-term wind power forecasting using Gaussian processes. Bristol Research (University of Bristol). 2790–2796. 26 indexed citations

Marcos, J. Víctor, Roberto Hornero, Ian T. Nabney, Daniel Álvarez, & Félix del Campo. (2011). Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. PubMed. 48. 1745–1748. 12 indexed citations

Calster, Ben Van, Ian T. Nabney, D. Timmerman, & Sabine Van Huffel. (2007). The Bayesian approach: a natural framework for statistical modeling. Ultrasound in Obstetrics and Gynecology. 29(5). 485–488. 3 indexed citations

Nabney, Ian T., et al.. (2006). A new entropy measure based on the Renyi entropy rate using Gaussian kernels. Aston Publications Explorer (Aston University). 2257. 187–209. 1 indexed citations

Nabney, Ian T., et al.. (2006). Visual data mining using principled projection algorithms and information visualization techniques. Bristol Research (University of Bristol). 9. 643–648. 8 indexed citations

Nabney, Ian T., et al.. (2005). EM algorithm for GTM-FS. Clinical Kidney Journal. 10(6). 747–758. 1 indexed citations

10.

Nabney, Ian T., et al.. (2005). Prediction of paroxysmal atrial fibrillation. Explore Bristol Research. 376–382. 3 indexed citations

11.

Nabney, Ian T., et al.. (2005). Semisupervised learning of hierarchical latent trait models for data visualization. IEEE Transactions on Knowledge and Data Engineering. 17(3). 384–400. 9 indexed citations

12.

Cornford, Dan, et al.. (2003). Outlier detection in scatterometer data: neural network approaches. Neural Networks. 16(3-4). 419–426. 14 indexed citations

13.

Nabney, Ian T., et al.. (2002). Analysing time series structure with hidden Markov models. Explore Bristol Research. 402–408. 7 indexed citations

14.

Tiňo, Peter & Ian T. Nabney. (2002). Hierarchical GTM: constructing localized nonlinear projection manifolds in a principled way. IEEE Transactions on Pattern Analysis and Machine Intelligence. 24(5). 639–656. 65 indexed citations

15.

Cornford, Dan, et al.. (2001). Improved neural network scatterometer forward models. Journal of Geophysical Research Atmospheres. 106(C10). 22331–22338. 13 indexed citations

16.

Evans, David J., Dan Cornford, & Ian T. Nabney. (2000). Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements. Neurocomputing. 30(1-4). 23–30. 7 indexed citations

17.

Cornford, Dan, Ian T. Nabney, & Chris Bishop. (1999). Neural Network-Based Wind Vector Retrieval from Satellite Scatterometer Data. Neural Computing and Applications. 8(3). 206–217. 27 indexed citations

18.

Cornford, Dan, Ian T. Nabney, & Christopher K. I. Williams. (1998). Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields. Aston Publications Explorer (Aston University). 11. 861–867. 6 indexed citations

19.

Nabney, Ian T., et al.. (1998). Delay Estimation for Multivariate Time Series. Aston Publications Explorer (Aston University). 1 indexed citations

20.

Bishop, Christopher & Ian T. Nabney. (1996). Modeling Conditional Probability Distributions for Periodic Variables. Neural Computation. 8(5). 1123–1133. 9 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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