Showing math.NAShow all
2 papers · 1 filter
math.NA2025
High-dimensional Bayesian filtering through deep density approximation
Kasper Bågmark, Filip Rydin
In this work, we systematically benchmark two recently developed deep density methods for nonlinear filtering. We model the filtering density of a discretely observed stochastic di…
math.NA2024
A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting
Kasper Bågmark, Adam Andersson, Stig Larsson +1
A numerical scheme for approximating the nonlinear filtering density is introduced and its convergence rate is established, theoretically under a parabolic Hörmander condition, and…