3 citations · 3 across the 1 of their papers we have counts for
Showing stat.COShow all
2 papers · 1 filter
stat.CO2024
Preserving linear invariants in ensemble filtering methods
Mathieu Le Provost, Jan Glaubitz, Youssef Marzouk
Data assimilation combines dynamical models with observations to improve state estimates. Ensemble filters sequentially assimilate observations by updating a set of samples over ti…
stat.CO2023★ 3 cited
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization
Mathieu Le Provost, Ricardo Baptista, Jeff D. Eldredge +1
Heavy tails is a common feature of filtering distributions that results from the nonlinear dynamical and observation processes as well as the uncertainty from physical sensors. In…