The Augmented Gaussian Sum Filter unifies Gaussian sum filters and particle filters via an augmented Gaussian approximation with tunable covariances that interpolates continuously between the two behaviors.
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pDANSE enables nonlinear state estimation for model-free processes by using RNN-parameterized Gaussian priors and reparameterization-based particle sampling to compute posterior second-order statistics from nonlinear measurements.
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A Gaussian Sum Filter for Unifying Gaussian and Particle Filters
The Augmented Gaussian Sum Filter unifies Gaussian sum filters and particle filters via an augmented Gaussian approximation with tunable covariances that interpolates continuously between the two behaviors.
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pDANSE: Particle-based Data-driven Nonlinear State Estimation from Nonlinear Measurements
pDANSE enables nonlinear state estimation for model-free processes by using RNN-parameterized Gaussian priors and reparameterization-based particle sampling to compute posterior second-order statistics from nonlinear measurements.