Joseph Lehec
- Applied Mathematics top 5%
- Statistics and Probability top 10%
- Artificial Intelligence
- Mathematical Physics
- Geometry and Topology
- Co-authors
- Bo’az KlartagRonen EldanSébastien BubeckCarsten SchüttMatthieu FradeliziOlivier GuédonElisabeth M. WernerNathaël Gozlan
- Topics
- Point processes and geometric inequalities (8 papers)Mathematical Inequalities and Applications (4 papers)Markov Chains and Monte Carlo Methods (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaBulletin of the American Mathematical SocietyThe Annals of Applied Probability
- Partner nations
- FranceIsraelUnited States
In The Last Decade
Joseph Lehec
13 papers receiving 133 citations
Peers
Comparison fields: 5 of 29
- Applied Mathematics 90
- Statistics and Probability 40
- Artificial Intelligence 25
- Mathematical Physics 18
- Geometry and Topology 17
Countries citing papers authored by Joseph Lehec
This map shows the geographic impact of Joseph Lehec'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 Joseph Lehec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph Lehec more than expected).
Fields of papers citing papers by Joseph Lehec
This network shows the impact of papers produced by Joseph Lehec. 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 Joseph Lehec. The network helps show where Joseph Lehec may publish in the future.
Co-authorship network of co-authors of Joseph Lehec
This figure shows the co-authorship network connecting the top 25 collaborators of Joseph Lehec. A scholar is included among the top collaborators of Joseph Lehec 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 Joseph Lehec. Joseph Lehec is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 25 | |
| 6 | 2 | |
| 7 | 7 | |
| 8 | Finite-time analysis of projected Langevin Monte Carlo | 5 |
| 9 | 28 | |
| 10 | 19 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | 19 | |
| 14 | 23 | |
| 15 | 3 |
About Joseph Lehec
Joseph Lehec is a scholar working on Applied Mathematics, Statistics and Probability and Geometry and Topology, having authored 15 papers that have together received 146 indexed citations. Recurring topics across this work include Point processes and geometric inequalities (8 papers), Mathematical Inequalities and Applications (4 papers) and Markov Chains and Monte Carlo Methods (3 papers). The work is most often cited by research in Applied Mathematics (90 citations), Statistics and Probability (40 citations) and Discrete Mathematics and Combinatorics (7 citations). Joseph Lehec has collaborated with scholars based in France, Israel and United States. Frequent co-authors include Bo’az Klartag, Ronen Eldan, Sébastien Bubeck, Carsten Schütt, Matthieu Fradelizi, Olivier Guédon, Elisabeth M. Werner, Nathaël Gozlan, Christian Léonard and André Schlichting. Their work appears in journals such as SHILAP Revista de lepidopterología, Bulletin of the American Mathematical Society and The Annals of Applied Probability.
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.