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Neural Kalman Filtering for Unknown Dynamics: Task-Aware Learning with a Koopman Backbone
Recent years have witnessed a growing interest in AI-aided Kalman filters. While emerging methodologies, such as KalmanNet, were shown to facilitate tracking in partially known state-space models, they are not directly applicable when the underlying dynamics is unknown. To overcome this limitation,
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