A unified meta-representation learned from past observations combined with state-feedback calibration enables general disturbance estimation with proven convergence.
Generalization of model- agnostic meta-learning algorithms: Recurring and unseen tasks
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Unified Meta-Representation and Feedback Calibration for General Disturbance Estimation
A unified meta-representation learned from past observations combined with state-feedback calibration enables general disturbance estimation with proven convergence.