3 citations · 3 across the 1 of their papers we have counts for
3 papers
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…
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…
Bayesian inference of vorticity in unbounded flow from limited pressure measurements
Jeff D. Eldredge, Mathieu Le Provost
We study the instantaneous inference of an unbounded planar flow from sparse noisy pressure measurements. The true flow field comprises one or more regularized point vortices of va…