A dynamic-graph GNN with element-wise attention (GATE) reports sub-2-meter mean Wi-Fi localization error across heterogeneous phones and buildings, outperforming published baselines.
Autonomous WiFi fingerprinting for indoor localization
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GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices
A dynamic-graph GNN with element-wise attention (GATE) reports sub-2-meter mean Wi-Fi localization error across heterogeneous phones and buildings, outperforming published baselines.