Jonathan Tepper
Impact in
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- Monetary Policy and Economic Impact
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- Stock Market Forecasting Methods
Papers in
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- Neural Networks and Applications 4
- Natural Language Processing Techniques 3
- Neural Networks and Reservoir Computing 3
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- Stock Market Forecasting Methods 8
- Co-authors
- Dominic Palmer-Brown (5 shared papers)Jane M. Binner (7 shared papers)Heather M. Powell (3 shared papers)T.M. McGinnity (2 shared papers)Mufti Mahmud (2 shared papers)Ahmad Lotfi (2 shared papers)Leo E. Hollister (1 shared paper)Chris Roadknight (3 shared papers)
- Journals
- Knowledge-Based Systems (2 papers)Cancer (1 paper)Artificial Intelligence in Medicine (1 paper)Trends in Cognitive Sciences (1 paper)Physica A Statistical Mechanics and its Applications (1 paper)
- Partner nations
- United KingdomUnited StatesSweden
In The Last Decade
Jonathan Tepper
21 papers receiving 192 citations
Peers
Comparison fields: 5 of 76
- General Economics, Econometrics and Finance 31
- Management Science and Operations Research 42
- Artificial Intelligence 70
- Economics and Econometrics 52
- Signal Processing 20
Countries citing papers authored by Jonathan Tepper
This map shows the geographic impact of Jonathan Tepper'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 Jonathan Tepper with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Tepper more than expected).
Fields of papers citing papers by Jonathan Tepper
This network shows the impact of papers produced by Jonathan Tepper. 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 Jonathan Tepper. The network helps show where Jonathan Tepper may publish in the future.
Co-authors
The 20 scholars most cited alongside Jonathan Tepper, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 32 | |
| 2 | The Myth of Capitalism: Monopolies and the Death of Competition | 2018 | 32 |
| 3 | 2006 | 21 | |
| 4 | 2010 | 17 | |
| 5 | 2002 | 14 | |
| 6 | 2020 | 14 | |
| 7 | 1978 | 13 | |
| 8 | 2004 | 12 | |
| 9 | 2016 | 10 | |
| 10 | Endgame: The End of the Debt SuperCycle and How It Changes Everything | 2011 | 9 |
| 11 | 2002 | 7 | |
| 12 | 2005 | 7 | |
| 13 | 2022 | 4 | |
| 14 | 2010 | 3 | |
| 15 | 2002 | 2 | |
| 16 | 2024 | 2 | |
| 17 | 2023 | 2 | |
| 18 | FAST LEARNING NEURAL NETS WITH ADAPTIVE LEARNING STYLES | 2003 | 2 |
| 19 | 2022 | 2 | |
| 20 | Characterizing the Magnetospheric State for Sawtooth Events | 2015 | 1 |
About Jonathan Tepper
Jonathan Tepper is a scholar working on Artificial Intelligence, Management Science and Operations Research, Economics and Econometrics, Molecular Biology and General Economics, Econometrics and Finance, having authored 25 papers that have together received 207 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (8 papers), Neural Networks and Applications (4 papers), Natural Language Processing Techniques (3 papers), Neural Networks and Reservoir Computing (3 papers), Complex Systems and Time Series Analysis (3 papers), Monetary Policy and Economic Impact (3 papers), Market Dynamics and Volatility (3 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in General Economics, Econometrics and Finance (31 citations), Management Science and Operations Research (42 citations), Artificial Intelligence (70 citations), Economics and Econometrics (52 citations) and Signal Processing (20 citations). Jonathan Tepper has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Dominic Palmer-Brown, Jane M. Binner, Heather M. Powell, T.M. McGinnity, Mufti Mahmud, Ahmad Lotfi, Leo E. Hollister, Chris Roadknight, Kenneth L. Davis and Graham Kendall. Their work appears in journals such as Knowledge-Based Systems, Cancer, Artificial Intelligence in Medicine, Trends in Cognitive Sciences and Physica A Statistical Mechanics and its Applications.
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.