FTimeXer improves power-grid carbon intensity forecasts by combining an FFT frequency branch with gated fusion and stochastic exogenous masking plus consistency regularization, showing gains on three real datasets.
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx
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FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting
FTimeXer improves power-grid carbon intensity forecasts by combining an FFT frequency branch with gated fusion and stochastic exogenous masking plus consistency regularization, showing gains on three real datasets.