STARQ uses a SegFormer-based multi-scale transformer with Gaussian-kernel pseudo-label propagation from sparse OpenAQ stations to downscale CAMS PM2.5 forecasts from 0.4° to 0.01° (~1 km) across Europe, achieving MAE 5.87 and R² 0.24 on held-out stations.
nature323(6088), 533–536 (1986)
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Hybrid quantum-classical networks match classical accuracy on tweet sentiment analysis and raise spam-class accuracy from 66% to 81% under transfer learning to SMS messages.
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Air Quality Downscaling with Station-Guided Pseudo-Supervision
STARQ uses a SegFormer-based multi-scale transformer with Gaussian-kernel pseudo-label propagation from sparse OpenAQ stations to downscale CAMS PM2.5 forecasts from 0.4° to 0.01° (~1 km) across Europe, achieving MAE 5.87 and R² 0.24 on held-out stations.
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Hybrid quantum-classical neural network for sentiment analysis
Hybrid quantum-classical networks match classical accuracy on tweet sentiment analysis and raise spam-class accuracy from 66% to 81% under transfer learning to SMS messages.