Browsing by Author "Jensen, Vilde"

Now showing items 1-2 of 2

    • Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting 

      Jensen, Vilde; Bianchi, Filippo Maria; Anfinsen, Stian Normann (Journal article; Tidsskriftartikkel, 2022-11-04)
      This article presents a novel probabilistic forecasting method called ensemble conformalized quantile regression (EnCQR). EnCQR constructs distribution-free and approximately marginally valid prediction intervals (PIs), which are suitable for nonstationary and heteroscedastic time series data. EnCQR can be applied on top of a generic forecasting model, including deep learning architectures. EnCQR ...

    • Probabilistic Load Forecasting with Deep Conformalized Quantile Regression 

      Jensen, Vilde (Master thesis; Mastergradsoppgave, 2021-06-01)
      The establishment of smart grids and the introduction of distributed generation posed new challenges in energy analytics that can be tackled with machine learning algorithms. The latter, are able to handle a combination of weather and consumption data, grid measurements, and their historical records to compute inference and make predictions. An accurate energy load forecasting is essential to assure ...