Loïc Cerf
Impact in
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- Parkinson's Disease Mechanisms and Treatments
- Neuroinflammation and Neurodegeneration Mechanisms
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- Data Management and Algorithms
Papers in
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- Algorithms and Data Compression 3
- Computational Physics and Python Applications 2
- Sentiment Analysis and Opinion Mining 1
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- Data Management and Algorithms 5
- Co-authors
- Alban Bessede (2 shared papers)José Á. Obeso (1 shared paper)Benjamin Dehay (1 shared paper)Carlos Matute (1 shared paper)Fabio Cavaliere (1 shared paper)Francesca De Giorgi (1 shared paper)Erwan Bézard (1 shared paper)Mathieu Bourdenx (1 shared paper)
- Journals
- Scientific Reports (1 paper)Data Mining and Knowledge Discovery (1 paper)Frontiers in Immunology (1 paper)International Journal of Computational Intelligence Systems (1 paper)Neurobiology of Disease (1 paper)
- Partner nations
- BrazilFranceUnited States
In The Last Decade
Loïc Cerf
10 papers receiving 224 citations
Peers
Comparison fields: 5 of 67
- Neurology 54
- Neurology 29
- Signal Processing 31
- Cellular and Molecular Neuroscience 40
- Biological Psychiatry 5
Countries citing papers authored by Loïc Cerf
This map shows the geographic impact of Loïc Cerf'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 Loïc Cerf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Loïc Cerf more than expected).
Fields of papers citing papers by Loïc Cerf
This network shows the impact of papers produced by Loïc Cerf. 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 Loïc Cerf. The network helps show where Loïc Cerf may publish in the future.
Co-authors
The 25 scholars most cited alongside Loïc Cerf, 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 | 2017 | 94 | |
| 2 | 2014 | 38 | |
| 3 | 2014 | 33 | |
| 4 | 2018 | 30 | |
| 5 | 2020 | 25 | |
| 6 | 2014 | 4 | |
| 7 | Constraint-Based Search of Straddling Biclusters and Discriminative Patterns | 2013 | 2 |
| 8 | 2011 | 2 | |
| 9 | 2019 | 2 | |
| 10 | 2018 | 1 | |
| 11 | Exploiting Temporal Locality to Determine User Bias in Microblogging Platforms | 2011 | 0 |
| 12 | 2020 | 0 |
About Loïc Cerf
Loïc Cerf is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Networks and Communications and Sociology and Political Science, having authored 12 papers that have together received 231 indexed citations. Recurring topics across this work include Data Management and Algorithms (5 papers), Data Mining Algorithms and Applications (3 papers), Algorithms and Data Compression (3 papers), Rough Sets and Fuzzy Logic (2 papers), Computational Physics and Python Applications (2 papers), Spam and Phishing Detection (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and Neurological disorders and treatments (1 paper). The work is most often cited by research in Neurology (54 citations), Neurology (29 citations), Signal Processing (31 citations), Cellular and Molecular Neuroscience (40 citations) and Biological Psychiatry (5 citations). Loïc Cerf has collaborated with scholars based in Brazil, France and United States. Frequent co-authors include Alban Bessede, José Á. Obeso, Benjamin Dehay, Carlos Matute, Fabio Cavaliere, Francesca De Giorgi, Erwan Bézard, Mathieu Bourdenx, François Ichas and Wagner Meira. Their work appears in journals such as Scientific Reports, Data Mining and Knowledge Discovery, Frontiers in Immunology, International Journal of Computational Intelligence Systems and Neurobiology of Disease.
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.