B³-Net improves multi-task dense prediction by estimating patch-wise evidence precision, fusing it into a reliability-weighted posterior bridge, and redistributing via bounded updates to limit contamination from unreliable task evidence.
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A unified deep learning model predicts FR3 signal strength from FR1 data and sparse measurements to cut simulation and measurement costs in 6G networks.
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$\mathcal{B}^{3}$-Net: Controlled Posterior Bridge Learning for Multi-Task Dense Prediction
B³-Net improves multi-task dense prediction by estimating patch-wise evidence precision, fusing it into a reliability-weighted posterior bridge, and redistributing via bounded updates to limit contamination from unreliable task evidence.
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CommUNext: Deep Learning-Based Cross-Band and Multi-Directional Signal Prediction
A unified deep learning model predicts FR3 signal strength from FR1 data and sparse measurements to cut simulation and measurement costs in 6G networks.