In linear detectable settings with nondegenerate noise, the MFEnKF contracts to the Gaussian subspace at explicit rates and its uniformly continuous moments coincide almost surely with the optimal filter in large time.
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2 Pith papers cite this work. Polarity classification is still indexing.
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A neural network approximates the velocity field of log-homotopy particle flow by enforcing a derived master PDE from the continuity equation, enabling unsupervised amortized Bayesian updates with reduced stiffness.
citing papers explorer
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Large-time behavior and accuracy of the Mean-Field Ensemble Kalman Filter in the Linear Detectable Setting
In linear detectable settings with nondegenerate noise, the MFEnKF contracts to the Gaussian subspace at explicit rates and its uniformly continuous moments coincide almost surely with the optimal filter in large time.
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Physics-informed neural particle flow for the Bayesian update step
A neural network approximates the velocity field of log-homotopy particle flow by enforcing a derived master PDE from the continuity equation, enabling unsupervised amortized Bayesian updates with reduced stiffness.