| Issue |
ESAIM: ProcS
Volume 65, 2019
CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field
|
|
|---|---|---|
| Page(s) | 68 - 83 | |
| DOI | https://doi.org/10.1051/proc/201965068 | |
| Published online | 02 April 2019 | |
New particle representations for ergodic McKean-Vlasov SDEs
1
IDP Laboratory, Orleans University, Orleans, France
2
Université Côte d'Azur, Inria, France
3
University of Florence, Italy
4
School of Mathematics, University of Edinburgh – Maxwell Institute for Mathematical Sciences, Edinburgh
5
The Alan Turing Institute, London
The aim of this paper is to introduce several new particle representations for ergodic McKean-Vlasov SDEs. We construct new algorithms by leveraging recent progress in weak convergence analysis of interacting particle system. We present detailed analysis of errors and associated costs of various estimators, highlighting key differences between long-time simulations of linear (classical SDEs) versus non-linear (Mckean-Vlasov SDEs) process.
© EDP Sciences, SMAI 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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