EMFusion applies conditional diffusion models with cross-attention and imputation sampling to deliver uncertainty-aware probabilistic forecasts for frequency-selective EMF data, outperforming baselines by 23.85% in CRPS.
Improved quantile convolutional neural network with two-stage training for daily-ahead probabilistic forecasting of photovoltaic power,
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EMFusion: An Uncertainty-Aware Conditional Diffusion Framework for Frequency-Selective EMF Forecasting in Wireless Networks
EMFusion applies conditional diffusion models with cross-attention and imputation sampling to deliver uncertainty-aware probabilistic forecasts for frequency-selective EMF data, outperforming baselines by 23.85% in CRPS.