jean-david.benamou@dauphine.psl.eu
Tel
: 0687794203
Bureau
: C616
JD Benamou est Directeur de Recherche INRIA et membre de l'équipe commune INRIA/CEREMADE MOKAPLAN. Ses centres d'intérêts sont le Transport Optimal et ses applications.
Benamou J-D., Chazareix G., Ijzerman W., Rukhaia G. (2022), Point Source Regularization of the Finite Source Reflector Problem, Journal of Computational Physics, n°456
Benamou J-D. (2021), Optimal transportation, modelling and numerical simulation, Acta Numerica, vol. 30, p. 249-325
Benamou J-D., Ijzerman W., Rukhaia G. (2020), An Entropic Optimal Transport Numerical Approach to the Reflector Problem, Methods and Applications of Analysis, vol. 27, n°4, p. 311 – 340
Benamou J-D., Gallouët T., Vialard F-X. (2019), Second order models for optimal transport and cubic splines on the Wasserstein space, Foundations of Computational Mathematics, n°19, p. 1113–1143
Benamou J-D., Carlier G., Nenna L. (2019), Generalized incompressible flows, multi-marginal transport and Sinkhorn algorithm, Numerische Mathematik, vol. 142, p. 33–54
Benamou J-D., Carlier G., Marino S., Nenna L. (2019), An entropy minimization approach to second-order variational mean-field games, Mathematical Models and Methods in Applied Sciences, vol. 29, n°8, p. 1553-1583
Duval V., Benamou J-D. (2018), Minimal convex extensions and finite difference discretisation of the quadratic Monge–Kantorovich problem, European Journal of Applied Mathematics, p. 1-38
Benamou J-D., Carlier G., Hatchi R. (2018), A numerical solution to Monge's problem with a Finsler distance as cost, ESAIM: Mathematical Modelling and Numerical Analysis, vol. 52, n°6 (November-December 2018 ), p. 2133 - 2148
Benamou J-D., Collino F., Mirebeau J-M. (2016), Monotone and Consistent discretization of the Monge-Ampere operator, Mathematics of Computation, vol. 85, p. 2743-2775
Benamou J-D., Carlier G., Mérigot Q., Oudet E. (2016), Discretization of functionals involving the Monge-Ampère operator, Numerische Mathematik, vol. 134, n°3, p. 611-636
Benamou J-D., Carlier G., Laborde M. (2016), An augmented Lagrangian approach to Wasserstein gradient flows and applications, ESAIM: Proceedings and Surveys, vol. 54, p. 1-17
Benamou J-D., Carlier G., Cuturi M., Nenna L., Peyré G. (2015), Iterative Bregman Projections for Regularized Transportation Problems, SIAM Journal on Scientific Computing, vol. 37, n°2, p. A1111–A1138
Benamou J-D., Carlier G. (2015), Augmented Lagrangian Methods for Transport Optimization, Mean Field Games and Degenerate Elliptic Equations, Journal of Optimization Theory and Applications, vol. 167, n°1, p. 1-26
Benamou J-D., Carlier G., Nenna L. (2017), A Numerical Method to Solve Multi-Marginal Optimal Transport Problems with Coulomb Cost, in Glowinski R., Osher S., Yin W., Splitting Methods in Communication, Imaging, Science, and Engineering Springer, p. 577-601
Benamou J-D., Carlier G., Santambrogio F. (2017), Variational Mean Field Games, in Nicola Bellomo, Pierre Degond, Eitan Tadmor, Active Particles, Volume 1, Paris: Springer, p. 141-171
Benamou J-D., Chazareix G., Loeper G. (2024), From entropic transport to martingale transport, and applications to model calibration, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 22 p.
Benamou J-D., Chazareix G., Hoffmann M., Loeper G., Vialard F-X. (2024), Entropic Semi-Martingale Optimal Transport, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL
Benamou J-D., Cotter C., Malamut H. (2023), Entropic Optimal Transport Solutions of the Semigeostrophic Equations, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 25 p.
Carlier G., Benamou J-D., Matthes D. (2023), Wasserstein gradient flow of the Fisher information from a non-smooth convex minimization viewpoint, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 21 p.
Benamou J-D., Froese B. (2014), A viscosity framework for computing Pogorelov solutions of the Monge-Ampere equation, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 24 p.
Benamou J-D., Bonne N., Carlier G. (2013), Une méthode numérique utilisant un Lagrangien augmenté pour la résolution de jeux à champs moyens, Il Mulino, 27 p.