Marc Vuffray
Impact in
- Mathematical Physics top 10%
- Advanced Mathematical Physics Problems
- Applied Mathematics top 10%
- Nonlinear Partial Differential Equations
Papers in ⓘ
-
- Quantum Information and Cryptography 7
- Quantum Computing Algorithms and Architecture 7
- Bayesian Modeling and Causal Inference 3
- Neural Networks and Reservoir Computing 2
- Co-authors
- Andrey Y. Lokhov (15 shared papers)Joachim Stubbe (2 shared papers)Sidhant Misra (8 shared papers)Nicolas Macris (5 shared papers)Vahid Aref (3 shared papers)Michael Chertkov (5 shared papers)Carleton Coffrin (9 shared papers)David Métivier (1 shared paper)
- Journals
- IEEE Transactions on Information Theory (2 papers)Physical Review Applied (1 paper)Differential and Integral Equations (1 paper)Quantum (1 paper)Science Advances (1 paper)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Marc Vuffray
23 papers receiving 236 citations
Peers
Comparison fields: 5 of 47
- Mathematical Physics 46
- Applied Mathematics 33
- Artificial Intelligence 81
- Statistical and Nonlinear Physics 31
- Computational Theory and Mathematics 40
Countries citing papers authored by Marc Vuffray
This map shows the geographic impact of Marc Vuffray'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 Marc Vuffray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Vuffray more than expected).
Fields of papers citing papers by Marc Vuffray
This network shows the impact of papers produced by Marc Vuffray. 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 Marc Vuffray. The network helps show where Marc Vuffray may publish in the future.
Co-authors
The 16 scholars most cited alongside Marc Vuffray, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 57 | |
| 2 | 2018 | 39 | |
| 3 | 2019 | 20 | |
| 4 | 2012 | 20 | |
| 5 | 2022 | 19 | |
| 6 | 2015 | 19 | |
| 7 | 2024 | 12 | |
| 8 | 2013 | 9 | |
| 9 | Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models | 2016 | 8 |
| 10 | 2020 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2010 | 5 | |
| 13 | 2023 | 3 | |
| 14 | 2024 | 3 | |
| 15 | 2018 | 3 | |
| 16 | 2023 | 2 | |
| 17 | 2012 | 2 | |
| 18 | 2014 | 2 | |
| 19 | Machine Learning for the Grid | 2016 | 2 |
| 20 | 2024 | 2 |
About Marc Vuffray
Marc Vuffray is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Networks and Communications, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, having authored 26 papers that have together received 245 indexed citations. Recurring topics across this work include Error Correcting Code Techniques (7 papers), Quantum Information and Cryptography (7 papers), Quantum Computing Algorithms and Architecture (7 papers), Advanced Wireless Communication Techniques (5 papers), Power System Optimization and Stability (3 papers), Quantum and electron transport phenomena (3 papers), Bayesian Modeling and Causal Inference (3 papers) and Neural Networks and Reservoir Computing (2 papers). The work is most often cited by research in Mathematical Physics (46 citations), Applied Mathematics (33 citations), Artificial Intelligence (81 citations), Statistical and Nonlinear Physics (31 citations) and Computational Theory and Mathematics (40 citations). Marc Vuffray has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Andrey Y. Lokhov, Joachim Stubbe, Sidhant Misra, Nicolas Macris, Vahid Aref, Michael Chertkov, Carleton Coffrin, David Métivier, Rüdiger Urbanke and Tameem Albash. Their work appears in journals such as IEEE Transactions on Information Theory, Physical Review Applied, Differential and Integral Equations, Quantum and Science Advances.
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.