most citedDifferentiable Particle Filtering using Optimal Placement Resampling

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cs.LG2026

Physics-informed neural particle flow for the Bayesian update step

Domonkos Csuzdi, Tamás Bécsi, Olivér Törő

The Bayesian update step poses significant computational challenges in high-dimensional nonlinear estimation. While log-homotopy particle flow filters offer an alternative to stoch…

cs.LG2024★ 2 cited

Differentiable Particle Filtering using Optimal Placement Resampling

Domonkos Csuzdi, Olivér Törő, Tamás Bécsi

Particle filters are a frequent choice for inference tasks in nonlinear and non-Gaussian state-space models. They can either be used for state inference by approximating the filter…