Bénédicte Haas

644 total citations
21 papers, 273 citations indexed

About

Bénédicte Haas is a scholar working on Mathematical Physics, Condensed Matter Physics and Statistics and Probability. According to data from OpenAlex, Bénédicte Haas has authored 21 papers receiving a total of 273 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Mathematical Physics, 10 papers in Condensed Matter Physics and 9 papers in Statistics and Probability. Recurrent topics in Bénédicte Haas's work include Stochastic processes and statistical mechanics (18 papers), Theoretical and Computational Physics (10 papers) and Markov Chains and Monte Carlo Methods (9 papers). Bénédicte Haas is often cited by papers focused on Stochastic processes and statistical mechanics (18 papers), Theoretical and Computational Physics (10 papers) and Markov Chains and Monte Carlo Methods (9 papers). Bénédicte Haas collaborates with scholars based in France, United Kingdom and Burundi. Bénédicte Haas's co-authors include Grégory Miermont, Jim Pitman, Matthias Winkel, Christina Goldschmidt, Nicolas Curien, Víctor M. Hernández Rivero, Igor Kortchemski, Julien Berestycki and Jean Bertoin and has published in prestigious journals such as The Annals of Probability, Probability Theory and Related Fields and Stochastic Processes and their Applications.

In The Last Decade

Bénédicte Haas

20 papers receiving 253 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bénédicte Haas France 10 249 96 96 50 35 21 273
Thomas Duquesne France 10 304 1.2× 120 1.3× 130 1.4× 36 0.7× 53 1.5× 20 326
Jean-François Le Gall France 4 196 0.8× 62 0.6× 74 0.8× 22 0.4× 28 0.8× 4 226
Augusto Teixeira Brazil 11 293 1.2× 139 1.4× 202 2.1× 11 0.2× 17 0.5× 26 311
Nathanaël Enriquez France 9 147 0.6× 45 0.5× 85 0.9× 12 0.2× 48 1.4× 30 204
Nikos Zygouras United Kingdom 9 276 1.1× 133 1.4× 214 2.2× 20 0.4× 61 1.7× 24 316
Peter Eichelsbacher Germany 10 133 0.5× 31 0.3× 179 1.9× 42 0.8× 59 1.7× 39 276
Igor Kortchemski France 8 156 0.6× 43 0.4× 77 0.8× 27 0.5× 7 0.2× 19 174
Jon Warren United Kingdom 8 156 0.6× 27 0.3× 154 1.6× 25 0.5× 21 0.6× 23 194
B. Maisonneuve France 7 128 0.5× 18 0.2× 50 0.5× 14 0.3× 75 2.1× 13 199
Artëm Sapozhnikov Netherlands 9 135 0.5× 72 0.8× 97 1.0× 5 0.1× 9 0.3× 22 181

Countries citing papers authored by Bénédicte Haas

Since Specialization
Citations

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

Fields of papers citing papers by Bénédicte Haas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bénédicte Haas

This figure shows the co-authorship network connecting the top 25 collaborators of Bénédicte Haas. A scholar is included among the top collaborators of Bénédicte Haas 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 Bénédicte Haas. Bénédicte Haas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Goldschmidt, Christina, et al.. (2022). Stable graphs: distributions and line-breaking construction. arXiv (Cornell University). 5. 841–904. 3 indexed citations
2.
Goldschmidt, Christina & Bénédicte Haas. (2016). Behavior near the extinction time in self-similar fragmentations II: Finite dislocation measures. The Annals of Probability. 44(1). 1 indexed citations
3.
Goldschmidt, Christina & Bénédicte Haas. (2015). A line-breaking construction of the stable trees. Electronic Journal of Probability. 20(none). 11 indexed citations
4.
Haas, Bénédicte, et al.. (2015). Scaling limits of $k$-ary growing trees. Annales de l Institut Henri Poincaré Probabilités et Statistiques. 51(4). 7 indexed citations
5.
Haas, Bénédicte. (2014). Asymptotics of heights in Rrandom trees constructed by aggregation. Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine). 1 indexed citations
6.
Curien, Nicolas, Bénédicte Haas, & Igor Kortchemski. (2014). The CRT is the scaling limit of random dissections. Random Structures and Algorithms. 47(2). 304–327. 16 indexed citations
7.
Haas, Bénédicte & Víctor M. Hernández Rivero. (2012). Quasi-stationary distributions and Yaglom limits of self-similar Markov processes. Stochastic Processes and their Applications. 122(12). 4054–4095. 14 indexed citations
8.
Haas, Bénédicte & Grégory Miermont. (2012). Scaling limits of Markov branching trees with applications to Galton–Watson and random unordered trees. The Annals of Probability. 40(6). 43 indexed citations
9.
Curien, Nicolas & Bénédicte Haas. (2012). The stable trees are nested. Probability Theory and Related Fields. 157(3-4). 847–883. 8 indexed citations
10.
Haas, Bénédicte & Grégory Miermont. (2011). Self-similar scaling limits of non-increasing Markov chains. Bernoulli. 17(4). 9 indexed citations
11.
Bertoin, Jean, et al.. (2010). Quelques interactions entre analyse, probabilités et fractals. Zurich Open Repository and Archive (University of Zurich). 32. 191–243.
12.
Goldschmidt, Christina & Bénédicte Haas. (2010). Behavior near the extinction time in self-similar fragmentations I: The stable case. Annales de l Institut Henri Poincaré Probabilités et Statistiques. 46(2). 3 indexed citations
13.
Haas, Bénédicte. (2010). Asymptotic behavior of solutions of the fragmentation equation with shattering: An approach via self-similar Markov processes. The Annals of Applied Probability. 20(2). 14 indexed citations
14.
Winkel, Matthias, Jim Pitman, Grégory Miermont, & Bénédicte Haas. (2009). Continuum tree asymptotics of discrete fragmentations and applications to phylogenetic models. Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine). 9 indexed citations
15.
Haas, Bénédicte, Jim Pitman, & Matthias Winkel. (2009). Spinal partitions and invariance under re-rooting of continuum random trees. The Annals of Probability. 37(4). 25 indexed citations
16.
Haas, Bénédicte. (2007). Fragmentation Processes with an Initial Mass Converging to Infinity. Journal of Theoretical Probability. 20(4). 721–758. 3 indexed citations
17.
Haas, Bénédicte. (2004). Regularity of formation of dust in self-similar fragmentations. Annales de l Institut Henri Poincaré Probabilités et Statistiques. 40(4). 411–438. 7 indexed citations
18.
Haas, Bénédicte. (2004). Appearance of dust in fragmentations. Communications in Mathematical Sciences. 2(5). 65–73. 5 indexed citations
19.
Haas, Bénédicte & Grégory Miermont. (2004). The Genealogy of Self-similar Fragmentations with Negative Index as a Continuum Random Tree. Electronic Journal of Probability. 9(none). 44 indexed citations
20.
Haas, Bénédicte. (2003). Loss of mass in deterministic and random fragmentations. Stochastic Processes and their Applications. 106(2). 245–277. 49 indexed citations

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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