Mathieu Laurière

1.3k total citations
44 papers, 400 citations indexed

About

Mathieu Laurière is a scholar working on Finance, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Mathieu Laurière has authored 44 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Finance, 12 papers in Economics and Econometrics and 11 papers in Artificial Intelligence. Recurrent topics in Mathieu Laurière's work include Stochastic processes and financial applications (21 papers), Economic theories and models (6 papers) and Quantum Computing Algorithms and Architecture (5 papers). Mathieu Laurière is often cited by papers focused on Stochastic processes and financial applications (21 papers), Economic theories and models (6 papers) and Quantum Computing Algorithms and Architecture (5 papers). Mathieu Laurière collaborates with scholars based in United States, France and China. Mathieu Laurière's co-authors include René Carmona, Olivier Pironneau, Yves Achdou, Tim Byrnes, Chandrashekar Radhakrishnan, Jean‐Pierre Fouque, Dante Kalise, Francisco J. Silva, Luis M. Briceño-Arias and Huyên Pham and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and European Journal of Operational Research.

In The Last Decade

Mathieu Laurière

41 papers receiving 391 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mathieu Laurière United States 12 168 112 77 76 66 44 400
Nigel J. Newton United Kingdom 9 226 1.3× 92 0.8× 45 0.6× 117 1.5× 32 0.5× 23 496
Paolo Dai Pra Italy 14 165 1.0× 65 0.6× 81 1.1× 176 2.3× 55 0.8× 58 681
Rafael Rigão Souza Brazil 6 117 0.7× 20 0.2× 72 0.9× 76 1.0× 32 0.5× 16 294
Benjamin Jourdain France 12 173 1.0× 32 0.3× 30 0.4× 46 0.6× 47 0.7× 56 496
Levon Nurbekyan United States 10 106 0.6× 79 0.7× 47 0.6× 129 1.7× 19 0.3× 23 365
Wilhelm Stannat Germany 13 254 1.5× 65 0.6× 23 0.3× 114 1.5× 45 0.7× 56 682
Steffen Dereich Germany 13 251 1.5× 61 0.5× 36 0.5× 109 1.4× 78 1.2× 38 589
Anna Gerardi Italy 10 137 0.8× 34 0.3× 40 0.5× 47 0.6× 47 0.7× 43 322
Aleksander Janicki Poland 7 139 0.8× 23 0.2× 91 1.2× 84 1.1× 23 0.3× 13 314
Daniel Lacker United States 12 443 2.6× 27 0.2× 240 3.1× 86 1.1× 89 1.3× 23 612

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-authorship network of co-authors of Mathieu Laurière

This figure shows the co-authorship network connecting the top 25 collaborators of Mathieu Laurière. A scholar is included among the top collaborators of Mathieu Laurière 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 Mathieu Laurière. Mathieu Laurière 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.
Laurière, Mathieu, et al.. (2025). A deep learning method for optimal investment under relative performance criteria among heterogeneous agents. European Journal of Operational Research. 326(3). 615–629.
2.
Guo, Xin, et al.. (2024). Connecting GANs, Mean-Field Games, and Optimal Transport. SIAM Journal on Applied Mathematics. 84(4). 1255–1287. 2 indexed citations
3.
Laurière, Mathieu, et al.. (2024). Recent developments in machine learning methods for stochastic control and games. Numerical Algebra Control and Optimization. 14(3). 435–525. 2 indexed citations
4.
Carmona, René, Mathieu Laurière, & Pierre‐Louis Lions. (2024). Nonstandard stochastic control with nonlinear Feynman–Kac costs. Illinois Journal of Mathematics. 68(3). 1 indexed citations
5.
Laurière, Mathieu, et al.. (2024). Deep learning for mean field optimal transport. SHILAP Revista de lepidopterología. 77. 145–175. 1 indexed citations
6.
Laurière, Mathieu, et al.. (2024). A Machine Learning Method for Stackelberg Mean Field Games. Mathematics of Operations Research. 50(4). 3055–3093. 2 indexed citations
7.
Laurière, Mathieu, et al.. (2024). Multi-population Mean Field Games with Multiple Major Players: Application to Carbon Emission Regulations. 5075–5081. 2 indexed citations
8.
Fouque, Jean‐Pierre, et al.. (2023). Reinforcement Learning Algorithm for Mixed Mean Field Control Games. 2(2). 108–137. 3 indexed citations
9.
Laurière, Mathieu, et al.. (2023). Policy Iteration Method for Time-Dependent Mean Field Games Systems with Non-separable Hamiltonians. Applied Mathematics & Optimization. 87(2). 6 indexed citations
10.
Laurière, Mathieu, et al.. (2023). Performance of a Markovian neural network versus dynamic programming on a fishing control problem. 8(1). 121–140. 1 indexed citations
11.
Carmona, René, et al.. (2022). Optimal Incentives to Mitigate Epidemics: A Stackelberg Mean Field Game Approach. SIAM Journal on Control and Optimization. 60(2). S294–S322. 35 indexed citations
12.
Carmona, René, et al.. (2022). Mean Field Models to Regulate Carbon Emissions in Electricity Production. Dynamic Games and Applications. 12(3). 897–928. 10 indexed citations
13.
Laurière, Mathieu, et al.. (2022). Recent Developments in Machine Learning Methods for Stochastic Control and Games. SSRN Electronic Journal. 8 indexed citations
14.
Guo, Xin, et al.. (2020). Connecting GANs and MFGs.. arXiv (Cornell University). 2 indexed citations
15.
Radhakrishnan, Chandrashekar, Mathieu Laurière, & Tim Byrnes. (2020). Multipartite Generalization of Quantum Discord. Physical Review Letters. 124(11). 110401–110401. 37 indexed citations
16.
Élie, Romuald, Julien Pérolat, Mathieu Laurière, Matthieu Geist, & Olivier Pietquin. (2019). Approximate Fictitious Play for Mean Field Games. arXiv (Cornell University). 5 indexed citations
17.
Huré, Côme, et al.. (2018). A Class of Finite-Dimensional Numerically Solvable McKean-Vlasov Control Problems. SHILAP Revista de lepidopterología. 7 indexed citations
18.
Briceño-Arias, Luis M., et al.. (2018). ON THE IMPLEMENTATION OF A PRIMAL-DUAL ALGORITHM FOR SECOND ORDER TIME-DEPENDENT MEAN FIELD GAMES WITH LOCAL COUPLINGS. SHILAP Revista de lepidopterología. 24 indexed citations
19.
Achdou, Yves & Mathieu Laurière. (2016). Mean Field Type Control with Congestion (II): An Augmented Lagrangian Method. Applied Mathematics & Optimization. 74(3). 535–578. 11 indexed citations
20.
Laurière, Mathieu & Olivier Pironneau. (2014). Dynamic programming for mean-field type control. Comptes Rendus Mathématique. 352(9). 707–713. 30 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Nigel J. Newton Breakdown of academic impact, for papers by Paolo Dai Pra Breakdown of academic impact, for papers by Rafael Rigão Souza Breakdown of academic impact, for papers by Benjamin Jourdain Breakdown of academic impact, for papers by Levon Nurbekyan Breakdown of academic impact, for papers by Wilhelm Stannat Breakdown of academic impact, for papers by Steffen Dereich Breakdown of academic impact, for papers by Anna Gerardi Breakdown of academic impact, for papers by Aleksander Janicki Breakdown of academic impact, for papers by Daniel Lacker
Rankless by CCL
2026