Nombre de documents

18


Article dans une revue10 documents

  • Michel Benaïm, Charles-Edouard Bréhier. Convergence of adaptive biasing potential methods for diffusions. Comptes Rendus Mathématique, Elsevier Masson, 2016, 354 (8), pp.842 - 846. 〈10.1016/j.crma.2016.05.011〉. 〈hal-01294029〉
  • Charles-Edouard Bréhier, Maxime Gazeau, Ludovic Goudenège, Tony Lelièvre, Mathias Rousset. Unbiasedness of some generalized adaptive multilevel splitting algorithms. The Annals of Applied Probability : an official journal of the institute of mathematical statistics, The Institute of Mathematical Statistics, 2016, 26 (6), pp.3559 - 3601. 〈10.1214/16-AAP1185〉. 〈hal-01142704〉
  • Charles-Edouard Bréhier, Ludovic Goudenège, Loic Tudela. Central Limit Theorem for Adaptative Multilevel Splitting Estimators in an Idealized Setting. Springer Proceedings in Mathematics & Statistics, Springer, 2016, Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April 2014, 163, pp.245--260. 〈http://dx.doi.org/10.1007/978-3-319-33507-0_10〉. 〈10.1007/978-3-319-33507-0_10〉. 〈hal-01074155〉
  • Charles-Edouard Bréhier, Gilles Vilmart. High Order Integrator for Sampling the Invariant Distribution of a Class of Parabolic Stochastic PDEs with Additive Space-Time Noise. SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2016, 38 (4), 〈10.1137/15M1021088〉. 〈hal-01153448v2〉
  • Charles-Edouard Bréhier, Marie Kopec. Approximation of the invariant law of SPDEs: error analysis using a Poisson equation for a full-discretization scheme. IMA Journal of Numerical Analysis, Oxford University Press (OUP), 2016, 〈10.1093/imanum/drw030〉. 〈hal-00910323v2〉
  • Charles-Edouard Bréhier, Erwan Faou. Analysis of the Monte-Carlo error in a hybrid semi-Lagrangian scheme. Applied Mathematics Research eXpress, Oxford University Press (OUP): Policy H - Oxford Open Option A, 2015, pp.167-203. 〈10.1093/amrx/abv001〉. 〈hal-00800133〉
  • Charles-Edouard Bréhier, Tony Lelièvre, Mathias Rousset. Analysis of Adaptive Multilevel Splitting algorithms in an idealized case. ESAIM: Probability and Statistics, EDP Sciences, 2015, 19, 〈10.1051/ps/2014029〉. 〈hal-00987297〉
  • Charles-Edouard Bréhier. Approximation of the invariant measure with an Euler scheme for Stochastic PDE's driven by Space-Time White Noise. Potential Analysis, Springer Verlag, 2014, 40 (1), pp.1-40. 〈10.1007/s11118-013-9338-9〉. 〈hal-00669462〉
  • Charles-Edouard Bréhier. Analysis of a HMM time-discretization scheme for a system of Stochastic PDE's. SIAM Journal on Numerical Analysis, Society for Industrial and Applied Mathematics, 2013, 51 (2), pp.1185-1210. 〈10.1137/110853078〉. 〈hal-00669470〉
  • Charles-Edouard Bréhier. Strong and weak order in averaging for SPDEs. Stochastic Processes and their Applications, Elsevier, 2012, 122 (7), pp.2553-2593. 〈10.1016/j.spa.2012.04.007〉. 〈hal-00669457〉

Pré-publication, Document de travail6 documents

  • Charles-Edouard Bréhier. Influence of the regularity of the test functions for weak convergence in numerical discretization of SPDEs. 2017. 〈hal-01595881〉
  • Charles-Edouard Bréhier, Arnaud Debussche. Kolmogorov Equations and Weak Order Analysis for SPDES with Nonlinear Diffusion Coefficient. 2017-22. 2017. 〈hal-01481966〉
  • Michel Benaïm, Charles-Edouard Bréhier. CONVERGENCE ANALYSIS OF ADAPTIVE BIASING POTENTIAL METHODS FOR DIFFUSION PROCESSES. 2017. 〈hal-01562639〉
  • Charles-Edouard Bréhier, Martin Hairer, Andrew M Stuart. Weak error estimates for trajectories of SPDEs for Spectral Galerkin discretization. 2016. 〈hal-01273500〉
  • Charles-Edouard Bréhier. A short introduction to Stochastic PDEs. The content is based on the lectures delivered at CERMICS in March 2014. 2014. 〈hal-00973887v2〉
  • Charles-Edouard Bréhier, Maxime Gazeau, Ludovic Goudenège, Mathias Rousset. Analysis and simulation of rare events for SPDE. 2014. 〈hal-00921680〉

Cours2 documents

  • Charles-Edouard Bréhier. LECTURE NOTES: INVARIANT DISTRIBUTIONS FOR PARABOLIC SPDEs AND THEIR NUMERICAL APPROXIMATIONS. Doctoral. Invariant distributions for parabolic SPDEs and their numerical approximations, Chinese Academy of Science, Beijing, China, France. 2017. 〈cel-01633504〉
  • Charles-Edouard Bréhier. Introduction to numerical methods for Ordinary Differential Equations. Licence. Introduction to numerical methods for Ordinary Differential Equations, Pristina, Kosovo, Serbia. 2016. 〈cel-01484274〉