Multilevel Monte Carlo in stochastic filtering
Dnr:
NAISS 2024/22-535
Type:
NAISS Small Compute
Principal Investigator:
Zheng Zhao
Affiliation:
Uppsala universitet
Start Date:
2024-04-09
End Date:
2025-05-01
Primary Classification:
10106: Probability Theory and Statistics
Webpage:
Allocation
Abstract
In this project we aim to explore the applicability of multilevel Monte Carlo in stochastic filtering. This is a basic research in the field of computational statistics, and the aim is to develop a parallelism scheme of multilevel Monte Carlo method, so that we can accelerate the compuation in stochastic filtering.