Daniel Revuz
Impact in
- Finance top 0.2%
- Stochastic processes and financial applications
- Financial Risk and Volatility Modeling
- Mathematical Physics top 0.2%
- Stochastic processes and statistical mechanics
- Mathematical Dynamics and Fractals
Papers in ⓘ
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- Advanced Topology and Set Theory 5
- Algebraic Geometry and Number Theory 2
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- Homotopy and Cohomology in Algebraic Topology 3
- advanced mathematical theories 1
Daniel Revuz
16 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Finance 3.0k
- Mathematical Physics 2.0k
- Statistics and Probability 838
- Applied Mathematics 692
- Modeling and Simulation 204
Countries citing papers authored by Daniel Revuz
This map shows the geographic impact of Daniel Revuz'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 Daniel Revuz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Revuz more than expected).
Fields of papers citing papers by Daniel Revuz
This network shows the impact of papers produced by Daniel Revuz. 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 Daniel Revuz. The network helps show where Daniel Revuz may publish in the future.
Co-authors
The 3 scholars most cited alongside Daniel Revuz, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Continuous Martingales and Brownian Motion Hit paper breakdown → | 1999 | 3341 |
| 2 | Continuous Martingales and Brownian Motion Hit paper breakdown → | 1991 | 1263 |
| 3 | 1970 | 78 | |
| 4 | 1967 | 76 | |
| 5 | 1969 | 20 | |
| 6 | Récurrence fine des processus de Markov | 1966 | 16 |
| 7 | 1970 | 14 | |
| 8 | Quelques applications probabilistes de la quasi-compacité | 1974 | 13 |
| 9 | 1970 | 13 | |
| 10 | Propriétés asymptotiques des probabilités de transition des processus de Markov récurrents | 1969 | 9 |
| 11 | 1971 | 4 | |
| 12 | 1974 | 4 | |
| 13 | Mesure et intégration | 1997 | 3 |
| 14 | 1978 | 3 | |
| 15 | 1976 | 2 | |
| 16 | 1973 | 2 | |
| 17 | 1970 | 1 | |
| 18 | 1974 | 1 | |
| 19 | Lois du tout ou rien et comportement asymptotique pour les probabilités de transition des processus de Markov | 1983 | 0 |
| 20 | 1977 | 0 |
About Daniel Revuz
Daniel Revuz is a scholar working on Geometry and Topology, Mathematical Physics, Statistics and Probability, Discrete Mathematics and Combinatorics and Computational Theory and Mathematics, having authored 21 papers that have together received 4.9k indexed citations. Recurring topics across this work include Advanced Topology and Set Theory (5 papers), Markov Chains and Monte Carlo Methods (3 papers), Homotopy and Cohomology in Algebraic Topology (3 papers), Petri Nets in System Modeling (2 papers), Algebraic Geometry and Number Theory (2 papers), advanced mathematical theories (1 paper), Social Sciences and Governance (1 paper) and Functional Equations Stability Results (1 paper). The work is most often cited by research in Finance (3.0k citations), Mathematical Physics (2.0k citations), Statistics and Probability (838 citations), Applied Mathematics (692 citations) and Modeling and Simulation (204 citations). Daniel Revuz has collaborated with scholars based in France. Frequent co-authors include Marc Yor, Marc Yor and Jacques Azéma. Their work appears in journals such as Probability Theory and Related Fields, Transactions of the American Mathematical Society, Annales de l’institut Fourier, Duke Mathematical Journal and Israel Journal of Mathematics.
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.