AutoPQ converts point forecasts into quantile forecasts with a conditional invertible neural network and automatically tunes both the uncertainty width and the point forecaster, beating six baseline methods on six smart grid datasets while reporting electricity consumption.
On the use of probabilistic forecasts in scheduling of renew- able energy sources coupled to storages,
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AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability
AutoPQ converts point forecasts into quantile forecasts with a conditional invertible neural network and automatically tunes both the uncertainty width and the point forecaster, beating six baseline methods on six smart grid datasets while reporting electricity consumption.