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Learning Graph Beliefs for Active Radio Mapping With Decision-Certified Multi-Step Sensing
Radio maps provide essential wireless propagation knowledge for network optimization and autonomous platforms. Acquiring dense measurements, however, is prohibitively costly, requiring active sampling to prioritize informative measurements. Existing active sampling methods typically rely on variance
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