A world-model-inspired active learning framework for RSSI map reconstruction outperforms Gaussian process interpolation by up to 5x lower RMSE in the few-shot regime on real indoor data.
Indoor radio map construction and localization with deep Gaussian processes,
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Radio Environment Mapping with World Models for Active Measurement Control: Should Networks Dream of Optimal Control?
A world-model-inspired active learning framework for RSSI map reconstruction outperforms Gaussian process interpolation by up to 5x lower RMSE in the few-shot regime on real indoor data.