Peggy Cénac

405 citations
18 papers · 137 · h-index 5

Impact in

Papers in

Peggy Cénac

16 papers receiving 131 citations

Peers

Peggy Cénac
Comparison fields: 5 of 51
  • Statistics and Probability 73
  • Mathematical Physics 17
  • Statistics, Probability and Uncertainty 13
  • Artificial Intelligence 56
  • Management Science and Operations Research 12
Replace Matthieu Lerasle with:
Matthieu Lerasle France
Qiyang Han United States
Cécile Durot France
Hannes Sieling Germany
Claire Lacour France
Motonobu Kanagawa Japan
Jonathan Weed United States
Jason M. Altschuler United States
Hiroyuki Shioya
Yu. V. Borovskich Ukraine
Peggy Cénac relative to Matthieu Lerasle France Matthieu Lerasle's profile →
Citations per field
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Matthieu Lerasle · 1×
Citations per year

Countries citing papers authored by Peggy Cénac

Since Specialization
Citations

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

Fields of papers citing papers by Peggy Cénac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Peggy Cénac, 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 Peggy Cénac Line = papers co-authored together Peggy Cénac links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201160
2 201136
3 20168
4 20127
5 20096
6
Fast clustering of large datasets with sequential $k$-medians : a stochastic gradient approach
20114
7 20054
8 20182
9
Dynamical Systems in the Analysis of Biological Sequences
20042
10 20112
11 20131
12 20241
13 20121
14 20091
15 20081
16 20201
17 20170
18
Convergence des moments dans le théorème de la limite centrale presque sûr pour les martingales vectorielles
20060

About Peggy Cénac

Peggy Cénac is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Finance and Management Science and Operations Research, having authored 18 papers that have together received 137 indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), Stochastic processes and financial applications (5 papers), Stochastic processes and statistical mechanics (4 papers), Probability and Risk Models (4 papers), Fractal and DNA sequence analysis (3 papers), Bayesian Methods and Mixture Models (3 papers), Advanced Clustering Algorithms Research (2 papers) and Mathematical Approximation and Integration (2 papers). The work is most often cited by research in Statistics and Probability (73 citations), Mathematical Physics (17 citations), Statistics, Probability and Uncertainty (13 citations), Artificial Intelligence (56 citations) and Management Science and Operations Research (12 citations). Peggy Cénac has collaborated with scholars based in France, United States and India. Frequent co-authors include Hervé Cardot, Pierre-André Zitt, Jean-Marie Monnez, Guy Fayolle, Bernard Bercu, Brigitte Chauvin, Véronique Maume‐Deschamps and Clémentine Prieur. Their work appears in journals such as Bernoulli, Journal of Applied Probability, Journal of Theoretical Probability, ESAIM Probability and Statistics and Random Structures and Algorithms.

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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