Anthony Bagnall

7.4k total citations · 6 hit papers
56 papers, 3.8k citations indexed

About

Anthony Bagnall is a scholar working on Artificial Intelligence, Signal Processing and Economics and Econometrics. According to data from OpenAlex, Anthony Bagnall has authored 56 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 33 papers in Signal Processing and 21 papers in Economics and Econometrics. Recurrent topics in Anthony Bagnall's work include Time Series Analysis and Forecasting (32 papers), Complex Systems and Time Series Analysis (20 papers) and Anomaly Detection Techniques and Applications (19 papers). Anthony Bagnall is often cited by papers focused on Time Series Analysis and Forecasting (32 papers), Complex Systems and Time Series Analysis (20 papers) and Anomaly Detection Techniques and Applications (19 papers). Anthony Bagnall collaborates with scholars based in United Kingdom, France and United States. Anthony Bagnall's co-authors include Jason Lines, James Large, Aaron Bostrom, Jon Hills, Eamonn Keogh, Matthew Middlehurst, Sarah Taylor, V. J. Rayward‐Smith, G. J. Janacek and Ian Whittley and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Cybernetics and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Anthony Bagnall

53 papers receiving 3.7k citations

Hit Papers

5 papers align trajectories

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.

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2016 801 citations Anthony Bagnall, Jason Lines et al. Data Mining and Knowledge Discovery profile →
Time series classification with ensembles of elastic distance measures

2014 333 citations Jason Lines, Anthony Bagnall Data Mining and Knowledge Discovery profile →
Classification of time series by shapelet transformation

2013 330 citations Jon Hills, Jason Lines et al. Data Mining and Knowledge Discovery profile →
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2020 285 citations Michael Flynn, James Large et al. Data Mining and Knowledge Discovery profile →
Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles

2015 277 citations Anthony Bagnall, Jason Lines et al. profile →
Bake off redux: a review and experimental evaluation of recent time series classification algorithms

2024 58 citations Matthew Middlehurst, Patrick Schäfer et al. Data Mining and Knowledge Discovery profile →

Peers

Anthony Bagnall

CVPR

Abdullah Mueen United States

Chotirat Ann Ratanamahatana Thailand

Pierre-Alain Müller France

Jessica Lin United States

James Clifford United States

Peter Scheuermann United States

Goce Trajcevski United States

Lhassane Idoumghar France

Kaushik Chakrabarti United States

François Petitjean Australia

Abdullah Mueen United States

Anthony Bagnall

2.9k ×1.1

2.2k ×0.9

641 ×0.9

535 ×1.8

CVPR

542 ×1.9

Citations per year, relative to Anthony Bagnall Anthony Bagnall (= 1×) peers Abdullah Mueen

Countries citing papers authored by Anthony Bagnall

Since Specialization

Citations

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

Fields of papers citing papers by Anthony Bagnall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anthony Bagnall

This figure shows the co-authorship network connecting the top 25 collaborators of Anthony Bagnall. A scholar is included among the top collaborators of Anthony Bagnall 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 Anthony Bagnall. Anthony Bagnall 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

Middlehurst, Matthew, Patrick Schäfer, & Anthony Bagnall. (2024). Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery. 38(4). 1958–2031. 58 indexed citations breakdown →

Bagnall, Anthony, Matthew Middlehurst, Germain Forestier, et al.. (2024). A Hands-on Introduction to Time Series Classification and Regression. ePrints Soton (University of Southampton). 6410–6411. 2 indexed citations

Guijo-Rubio, David, et al.. (2024). Convolutional- and Deep Learning-Based Techniques for Time Series Ordinal Classification. IEEE Transactions on Cybernetics. 55(2). 537–549. 2 indexed citations

Middlehurst, Matthew, Patrick Schäfer, & Anthony Bagnall. (2024). Correction: Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery. 38(6). 4236–4237. 6 indexed citations

Guijo-Rubio, David, et al.. (2024). Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery. 38(4). 2141–2185. 2 indexed citations

Ifrim, Georgiana, Romain Tavenard, Anthony Bagnall, et al.. (2023). Advanced Analytics and Learning on Temporal Data. Lecture notes in computer science. 1 indexed citations

Middlehurst, Matthew, et al.. (2022). A Review and Evaluation of Elastic Distance Functions for Time Series Clustering. arXiv (Cornell University). 1 indexed citations

Flynn, Michael, et al.. (2020). The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery. 35(2). 401–449. 285 indexed citations breakdown →

Guijo-Rubio, David, Pedro Antonio Gutiérrez, Anthony Bagnall, & César Hervás‐Martínez. (2020). Time series ordinal classification via shapelets. UEA Digital Repository (University of East Anglia). 1–8. 4 indexed citations

10.

Large, James, Jason Lines, & Anthony Bagnall. (2019). A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates. Data Mining and Knowledge Discovery. 33(6). 1674–1709. 54 indexed citations

11.

Dau, Hoang Anh, Diego Furtado Silva, François Petitjean, et al.. (2018). Optimizing dynamic time warping’s window width for time series data mining applications. Data Mining and Knowledge Discovery. 32(4). 1074–1120. 58 indexed citations

12.

Lines, Jason & Anthony Bagnall. (2014). Ensembles of Elastic Distance Measures for Time Series Classification. 17 indexed citations

13.

Bagnall, Anthony, Luke M. Davis, Jon Hills, & Jason Lines. (2012). Transformation Based Ensembles for Time Series Classification. 307–318. 65 indexed citations

14.

Bagnall, Anthony, et al.. (2012). An efficient randomised sphere cover classifier. International Journal of Data Mining Modelling and Management. 4(2). 156–156. 6 indexed citations

15.

Toms, Andoni P., et al.. (2011). Physiology of the small bowel: A new approach using MRI and proposal for a new metric of function. Medical Hypotheses. 76(6). 834–839. 3 indexed citations

16.

Bagnall, Anthony, Simon Moxon, & David J. Studholme. (2008). Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. UEA Digital Repository (University of East Anglia). 182–188. 2 indexed citations

17.

Bagnall, Anthony, et al.. (2006). A Comparison of DWT/PAA and DFT for Time Series Classification. UWE Research Repository (UWE Bristol). 403–409.

18.

Bagnall, Anthony, et al.. (2005). AgentP Classifier System: self-adjusting vs. gradual approach. UEA Digital Repository (University of East Anglia). 2. 1196–1203. 4 indexed citations

19.

Bagnall, Anthony. (2000). A multi-adaptive agent model of generator bidding in the UK market in electricity. Genetic and Evolutionary Computation Conference. 605–612. 26 indexed citations

20.

Bagnall, Anthony, et al.. (1997). The Cryptanalysis of a Three Rotor Machine Using a Genetic Algorithm.. 69(1781). 712–718. 17 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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