Frédéric Lavancier

23 papers receiving 266 citations

Peers

Frédéric Lavancier
Comparison fields: 5 of 60
  • Statistics and Probability 100
  • Applied Mathematics 112
  • Mathematical Physics 55
  • Finance 60
  • Geometry and Topology 22
Replace Irina Shevtsova with:
Irina Shevtsova Russia
Pavlo O. Kasyanov Ukraine
S. Y. Novak United Kingdom
Ion Grama France
Valery A. Kalyagin Russia
N. G. Ushakov Russia
Alessandro De Gregorio Italy
Sylvain Delattre France
V. Statulevičius Lithuania
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Citations per year

Countries citing papers authored by Frédéric Lavancier

Since Specialization
Citations

This map shows the geographic impact of Frédéric Lavancier'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 Frédéric Lavancier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédéric Lavancier more than expected).

Fields of papers citing papers by Frédéric Lavancier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frédéric Lavancier. 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 Frédéric Lavancier. The network helps show where Frédéric Lavancier may publish in the future.

Co-authors

The 13 scholars most cited alongside Frédéric Lavancier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Frédéric Lavancier Line = papers co-authored together Frédéric Lavancier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201498
2 201531
3 200930
4 200719
5 201618
6 20159
7 20109
8 20109
9 20139
10 20158
11 20167
12 20216
13 20064
14 20084
15 20143
16
About repulsiveness of determinantal point processes
20142
17 20172
18 20172
19 20231
20 20121

About Frédéric Lavancier

Frédéric Lavancier is a scholar working on Applied Mathematics, Statistics and Probability, Finance, Artificial Intelligence and Economics and Econometrics, having authored 26 papers that have together received 276 indexed citations. Recurring topics across this work include Point processes and geometric inequalities (14 papers), Random Matrices and Applications (6 papers), Financial Risk and Volatility Modeling (6 papers), Complex Systems and Time Series Analysis (5 papers), Bayesian Methods and Mixture Models (5 papers), Stochastic processes and financial applications (4 papers), Morphological variations and asymmetry (4 papers) and Market Dynamics and Volatility (3 papers). The work is most often cited by research in Statistics and Probability (100 citations), Applied Mathematics (112 citations), Mathematical Physics (55 citations), Finance (60 citations) and Geometry and Topology (22 citations). Frédéric Lavancier has collaborated with scholars based in France, Denmark and Lithuania. Frequent co-authors include Jesper Möller, Ege Rubak, Christophe A. N. Biscio, Anne Philippe, Донатас Сургайлис, Ronan Le Guével, Remigijus Leipus, Jean‐François Coeurjolly, Rémi Bardenet and Xavier Mary. Their work appears in journals such as Scandinavian Journal of Statistics, Computational Statistics & Data Analysis, Electronic Journal of Statistics, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Bernoulli.

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.

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