Mathieu Laurière

1.5k citations
55 papers · 600 · h-index 16

Impact in

    • Mathematical Biology Tumor Growth
    • COVID-19 epidemiological studies
  • Finance top 5%
    • Stochastic processes and financial applications

Papers in

Mathieu Laurière

50 papers receiving 590 citations

Peers

Mathieu Laurière
Comparison fields: 5 of 66
  • Modeling and Simulation 108
  • Finance 230
  • Statistical and Nonlinear Physics 115
  • Management Science and Operations Research 108
  • Mathematical Physics 54
Replace Thomas Kruse with:
Thomas Kruse Germany
Claudio Macci Italy
Łukasz Szpruch United Kingdom
Romuald Élie France
Xavier Warin France
Levon Nurbekyan United States
Rafael Rigão Souza Brazil
Daniel Lacker United States
Gopal K. Basak India
Sotirios Sabanis United Kingdom
Mathieu Laurière relative to Thomas Kruse Germany Thomas Kruse's profile →
Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Mathieu Laurière

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Laurière

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mathieu Laurière, 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 Mathieu Laurière Line = papers co-authored together Mathieu Laurière links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202041
2 202240
3 202040
4 202239
5 202038
6 201438
7 202229
8 202228
9 201826
10 202025
11 202225
12 201523
13 201519
14 202218
15 201616
16 202315
17 201614
18 202210
19 20229
20
Approximate Fictitious Play for Mean Field Games
20198

About Mathieu Laurière

Mathieu Laurière is a scholar working on Finance, Economics and Econometrics, Artificial Intelligence, Management Science and Operations Research and Statistical and Nonlinear Physics, having authored 55 papers that have together received 600 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (22 papers), Economic theories and models (7 papers), Quantum Computing Algorithms and Architecture (5 papers), Quantum Information and Cryptography (5 papers), Climate Change Policy and Economics (5 papers), Markov Chains and Monte Carlo Methods (4 papers), Mathematical Biology Tumor Growth (4 papers) and Reinforcement Learning in Robotics (4 papers). The work is most often cited by research in Modeling and Simulation (108 citations), Finance (230 citations), Statistical and Nonlinear Physics (115 citations), Management Science and Operations Research (108 citations) and Mathematical Physics (54 citations). Mathieu Laurière has collaborated with scholars based in United States, France and China. Frequent co-authors include René Carmona, Yves Achdou, Olivier Pironneau, Romuald Élie, Chandrashekar Radhakrishnan, Tim Byrnes, Viet Chi Tran, Arthur Charpentier, Jean‐Pierre Fouque and Matthieu Geist. Their work appears in journals such as Applied Mathematics & Optimization, SIAM Journal on Control and Optimization, The Annals of Applied Probability, Algorithmica and SIAM Journal on Applied 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.

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