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A novel deep transfer learning framework for forecasting NavIC satellite ephemeris and clock errors. PRESTO overcomes extreme data scarcity using a hybrid architecture (GNNs + Semiparametric Decomposition + Autoformers) and synthetic data augmentation to generate normally distributed prediction residuals.
A novel deep transfer learning framework for forecasting NavIC satellite ephemeris and clock errors. PRESTO overcomes extreme data scarcity using a hybrid architecture (GNNs + Semiparametric Decomposition + Autoformers) and synthetic data augmentation to generate normally distributed prediction residuals.