Delphine Salort
- Statistical and Nonlinear Physics top 5%
- Cognitive Neuroscience top 10%
- Computer Networks and Communications top 10%
- Applied Mathematics top 5%
- Molecular Biology
- Co-authors
- Benoı̂t PerthameKhashayar PakdamanDidier SmetsJosé A. CarrilloMaría J. CáceresHirokazu TanimotoDaria BonazziBertrand Maury
- Topics
- stochastic dynamics and bifurcation (16 papers)Neural dynamics and brain function (13 papers)Advanced Mathematical Physics Problems (8 papers)
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
Delphine Salort
34 papers receiving 350 citations
Peers
Comparison fields: 5 of 55
- Statistical and Nonlinear Physics 212
- Cognitive Neuroscience 147
- Computer Networks and Communications 99
- Applied Mathematics 63
- Molecular Biology 59
Countries citing papers authored by Delphine Salort
This map shows the geographic impact of Delphine Salort'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 Delphine Salort with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Delphine Salort more than expected).
Fields of papers citing papers by Delphine Salort
This network shows the impact of papers produced by Delphine Salort. 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 Delphine Salort. The network helps show where Delphine Salort may publish in the future.
Co-authorship network of co-authors of Delphine Salort
This figure shows the co-authorship network connecting the top 25 collaborators of Delphine Salort. A scholar is included among the top collaborators of Delphine Salort 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 Delphine Salort. Delphine Salort is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 7 | |
| 3 | 4 | |
| 4 | 6 | |
| 5 | 9 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 10 | |
| 9 | Derivation of an integrate&fire equation for neural networks from a voltage-conductance kinetic model | 1 |
| 10 | 7 | |
| 11 | 6 | |
| 12 | 20 | |
| 13 | 4 | |
| 14 | 30 | |
| 15 | 38 | |
| 16 | 21 | |
| 17 | 5 | |
| 18 | 14 | |
| 19 | 4 | |
| 20 | 1 |
About Delphine Salort
Delphine Salort is a scholar working on Statistical and Nonlinear Physics, Mathematical Physics and Applied Mathematics, having authored 34 papers that have together received 361 indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (16 papers), Neural dynamics and brain function (13 papers) and Advanced Mathematical Physics Problems (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (212 citations), Cognitive Neuroscience (147 citations) and Modeling and Simulation (35 citations). Delphine Salort has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Benoı̂t Perthame, Khashayar Pakdaman, Didier Smets, José A. Carrillo, María J. Cáceres, Hirokazu Tanimoto, Daria Bonazzi, Bertrand Maury, Ayman Moussa and Delphine Delacour. Their work appears in journals such as Current Biology, European Journal of Operational Research and Physica D Nonlinear Phenomena.
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.