Gabriel Turinici
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Gabriel Turinici has a total of 100 co-authors. Here are the top co-authors by number of shared publications:
- Herschel Rabitz
Department of Chemistry, Princeton University, Princeton, USA
12 shared publications - Antoine Danchin
School of Biomedical Sciences, Li KaShing Faculty of Medicine The University of Hong Kong SAR Hong Kong China
10 shared publications Herschel Rabitz
Department of Chemistry, Princeton University, NJ 08544, USA
9 shared publicationsYvon Maday
9 shared publications- Yvon Maday
Laboratoire Jacques-Louis Lions (LJLL), Sorbonne Université, CNRS, Université Paris Cité, F-75005 Paris, France
7 shared publications Julien Salomon
6 shared publications
Latest Publications
- 25 March 2026
- Published by Springer Nature in Annals of Finance
- Vol. 22 (1) , 6
Onflow: a model free, online portfolio allocation algorithm robust to transaction fees
- 25 March 2026
- Published by Springer Nature in Annals of Finance
- Vol. 22 (1) , 6
Onflow: a model free, online portfolio allocation algorithm robust to transaction fees
- 13 August 2025
- Published by Springer Nature in Decisions in Economics and Finance
- p. 1-30
High order universal portfolios
- 13 August 2025
- Published by Springer Nature in Decisions in Economics and Finance
- p. 1-30
High order universal portfolios
- 15 July 2025
- Published by Elsevier in Journal of Computational and Applied Mathematics
- Vol. 473
Regime-aware time weighting for physics-informed neural networks
- 15 July 2025
- Published by Elsevier in Journal of Computational and Applied Mathematics
- Vol. 473
Regime-aware time weighting for physics-informed neural networks
- 7 March 2025
- Published by Springer Nature
- p. 511-528
Transformer for Time Series: An Application to the S&P500
- 7 March 2025
- Published by Springer Nature
- p. 511-528
Transformer for Time Series: An Application to the S&P500
- 27 February 2025
- Published by Springer Nature in Bollettino dell'Unione Matematica Italiana
- Vol. 18 (4) , 1171-1179
The impact of recovery rate heterogeneity in achieving herd immunity
- 27 February 2025
- Published by Springer Nature in Bollettino dell'Unione Matematica Italiana
- Vol. 18 (4) , 1171-1179
The impact of recovery rate heterogeneity in achieving herd immunity
- 3 December 2024
- Published by Springer Nature
- p. 407-422
Convergence of a L2 Regularized Policy Gradient Algorithm for the Multi Armed Bandit
- 3 December 2024
- Published by Springer Nature
- p. 407-422
Convergence of a L2 Regularized Policy Gradient Algorithm for the Multi Armed Bandit
- 3 December 2024
- Published by Springer Nature
- p. 218-233
Optimal Time Sampling in Physics-Informed Neural Networks
- 3 December 2024
- Published by Springer Nature
- p. 218-233
Optimal Time Sampling in Physics-Informed Neural Networks
- 25 November 2024
- Published by Springer Nature in Statistics and Computing
- Vol. 35 (1) , 1-22
Huber-energy measure quantization
- 25 November 2024
- Published by Springer Nature in Statistics and Computing
- Vol. 35 (1) , 1-22
Huber-energy measure quantization
- Open Access
Individual vaccination as Nash equilibrium in a SIR model with application to the 2009-10 Influenza A(H1N1) epidemic in France
The vaccination against ongoing epidemics is seldom compulsory but remains one of the most classical means to fight epidemic propagation. However recent debates concerning the innocuity of vaccines and their risk with respect to the risk of the epidemic itself lead to severe vaccination campaign failures and new mass behaviors appeared driven by individual self-interest. Prompted by this context we analyze, in a Susceptible-Infected-Recovered (SIR) model, whether egocentric individuals can reach an equilibrium with the rest of the society. Using techniques from the "Mean Field Games" theory, we extend previous results and show that an equilibrium exists and characterizes completely the individual best vaccination strategy (with or without discounting). We also compare with a strategy based only on overall societal optimization and exhibit a situation with non-negative price of anarchy. Finally, we apply the theory to the 2009-2010 Influenza A (H1N1) vaccination campaign in France and hint that a group of individuals stopped vaccinating at levels that indicated a pessimistic perception of the risk of the vaccine.
Open AccessIndividual vaccination as Nash equilibrium in a SIR model with application to the 2009-10 Influenza A(H1N1) epidemic in France
The vaccination against ongoing epidemics is seldom compulsory but remains one of the most classical means to fight epidemic propagation. However recent debates concerning the innocuity of vaccines and their risk with respect to the risk of the epidemic itself lead to severe vaccination campaign failures and new mass behaviors appeared driven by individual self-interest. Prompted by this context we analyze, in a Susceptible-Infected-Recovered (SIR) model, whether egocentric individuals can reach an equilibrium with the rest of the society. Using techniques from the "Mean Field Games" theory, we extend previous results and show that an equilibrium exists and characterizes completely the individual best vaccination strategy (with or without discounting). We also compare with a strategy based only on overall societal optimization and exhibit a situation with non-negative price of anarchy. Finally, we apply the theory to the 2009-2010 Influenza A (H1N1) vaccination campaign in France and hint that a group of individuals stopped vaccinating at levels that indicated a pessimistic perception of the risk of the vaccine.
- 6 September 2024
- Published by Elsevier in Journal of Quantitative Spectroscopy and Radiative Transfer
- Vol. 329
The Quantization Monte Carlo method for solving radiative transport equations
- 6 September 2024
- Published by Elsevier in Journal of Quantitative Spectroscopy and Radiative Transfer
- Vol. 329
The Quantization Monte Carlo method for solving radiative transport equations