James Large
Impact in
- Signal Processing top 0.5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
- Neural Networks and Applications
Papers in ⓘ
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- Anomaly Detection Techniques and Applications 4
- Machine Learning and Data Classification 1
- Advanced Text Analysis Techniques 1
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- Time Series Analysis and Forecasting 4
- Co-authors
- Anthony Bagnall (5 shared papers)Jason Lines (2 shared papers)Eamonn Keogh (1 shared paper)Aaron Bostrom (1 shared paper)Matthew Middlehurst (2 shared papers)Michael Flynn (1 shared paper)Apostolos Pesyridis (1 shared paper)Simon Malinowski (1 shared paper)
- Journals
- Data Mining and Knowledge Discovery (3 papers)Aerospace (1 paper)Intelligent Data Analysis (1 paper)UEA Digital Repository (University of East Anglia) (1 paper)
- Partner nations
- United KingdomFranceUnited States
In The Last Decade
James Large
8 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Signal Processing 909
- Artificial Intelligence 750
- Economics and Econometrics 202
- Management Science and Operations Research 84
- Computer Vision and Pattern Recognition 105
Countries citing papers authored by James Large
This map shows the geographic impact of James Large'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 Large with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Large more than expected).
Fields of papers citing papers by James Large
This network shows the impact of papers produced by James Large. 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 Large. The network helps show where James Large may publish in the future.
Co-authors
The 9 scholars most cited alongside James Large, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances Hit paper breakdown → | 2016 | 801 |
| 2 | The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances Hit paper breakdown → | 2020 | 285 |
| 3 | 2020 | 62 | |
| 4 | 2019 | 54 | |
| 5 | 2019 | 44 | |
| 6 | 2019 | 27 | |
| 7 | The foreign-language barrier : problems in scientific communication | 1983 | 22 |
| 8 | The foreign-language barrier | 1983 | 12 |
About James Large
James Large is a scholar working on Artificial Intelligence, Signal Processing, Economics and Econometrics, Information Systems and Computational Mechanics, having authored 8 papers that have together received 1.3k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (4 papers), Anomaly Detection Techniques and Applications (4 papers), Complex Systems and Time Series Analysis (3 papers), Scientific Research and Philosophical Inquiry (1 paper), Combustion and Detonation Processes (1 paper), Machine Learning and Data Classification (1 paper), Combustion and flame dynamics (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (909 citations), Artificial Intelligence (750 citations), Economics and Econometrics (202 citations), Management Science and Operations Research (84 citations) and Computer Vision and Pattern Recognition (105 citations). James Large has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Anthony Bagnall, Jason Lines, Eamonn Keogh, Aaron Bostrom, Matthew Middlehurst, Michael Flynn, Apostolos Pesyridis, Simon Malinowski and Romain Tavenard. Their work appears in journals such as Data Mining and Knowledge Discovery, Aerospace, Intelligent Data Analysis and UEA Digital Repository (University of East Anglia).
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.