Éric Séverin
Impact in
- Accounting top 2%
- Financial Distress and Bankruptcy Prediction
- Corporate Finance and Governance
- Auditing, Earnings Management, Governance
- Artificial Intelligence top 5%
- Machine Learning and ELM
- Imbalanced Data Classification Techniques
- Neural Networks and Applications
Papers in
- Accounting 26
- Financial Distress and Bankruptcy Prediction 15
- Corporate Finance and Governance 10
- Auditing, Earnings Management, Governance 8
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- Machine Learning and ELM 11
- Neural Networks and Applications 9
- Imbalanced Data Classification Techniques 5
- Co-authors
- David Veganzones (14 shared papers)Yoan Miché (14 shared papers)Amaury Lendasse (12 shared papers)Qi Yu (8 shared papers)Philippe du Jardin (6 shared papers)Mark van Heeswijk (2 shared papers)Sture Nordholm (1 shared paper)Emil Eirola (3 shared papers)
In The Last Decade
Éric Séverin
40 papers receiving 927 citations
Peers
Comparison fields: 5 of 93
- Accounting 393
- Artificial Intelligence 509
- Finance 109
- Management Science and Operations Research 125
- Strategy and Management 70
Countries citing papers authored by Éric Séverin
This map shows the geographic impact of Éric Séverin'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 Éric Séverin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éric Séverin more than expected).
Fields of papers citing papers by Éric Séverin
This network shows the impact of papers produced by Éric Séverin. 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 Éric Séverin. The network helps show where Éric Séverin may publish in the future.
Co-authors
The 25 scholars most cited alongside Éric Séverin, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 147 | |
| 2 | 2012 | 106 | |
| 3 | 2013 | 106 | |
| 4 | 1978 | 94 | |
| 5 | 2013 | 90 | |
| 6 | 2011 | 76 | |
| 7 | 2020 | 48 | |
| 8 | 2013 | 33 | |
| 9 | 2017 | 31 | |
| 10 | 2021 | 27 | |
| 11 | 2021 | 26 | |
| 12 | 2010 | 19 | |
| 13 | 2010 | 17 | |
| 14 | 2015 | 16 | |
| 15 | 2001 | 16 | |
| 16 | 2021 | 14 | |
| 17 | Variable Selection for Financial Modeling | 2007 | 12 |
| 18 | Ensembles of Local Linear Models for Bankruptcy Analysis and Prediction | 2011 | 11 |
| 19 | 2015 | 9 | |
| 20 | 2014 | 8 |
About Éric Séverin
Éric Séverin is a scholar working on Accounting, Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition and Finance, having authored 45 papers that have together received 963 indexed citations. Recurring topics across this work include Financial Distress and Bankruptcy Prediction (15 papers), Machine Learning and ELM (11 papers), Corporate Finance and Governance (10 papers), Neural Networks and Applications (9 papers), Auditing, Earnings Management, Governance (8 papers), Stock Market Forecasting Methods (7 papers), Face and Expression Recognition (7 papers) and Imbalanced Data Classification Techniques (5 papers). The work is most often cited by research in Accounting (393 citations), Artificial Intelligence (509 citations), Finance (109 citations), Management Science and Operations Research (125 citations) and Strategy and Management (70 citations). Éric Séverin has collaborated with scholars based in France, Finland and Spain. Frequent co-authors include David Veganzones, Yoan Miché, Amaury Lendasse, Qi Yu, Philippe du Jardin, Mark van Heeswijk, Sture Nordholm, Emil Eirola, Donn L. Jolly and Ben C. Freasier. Their work appears in journals such as Neurocomputing, Decision Support Systems, European Business Review, Annals of Operations Research and Chemical Physics Letters.
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.