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NANO: A Unified Optimization Framework for Nonlinear Gaussian Filtering
Conventional Gaussian filtering typically approximates nonlinear models or their statistical moments and retains the Kalman update structure. The resulting approximation errors can affect both state estimates and their uncertainty. This paper presents the Natural Gradient Gaussian Approximation (NAN
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