
This paper proposes a nonparametric end-to-end method for probabilistic forecasting of distributed renewable generation outputs that effectively handles missing data through iterative imputation and end-to-end training.


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nonparametric-end-to-end-probabilistic-forecasting-of-distributed-generation-outputs-with-missing-data-imputation


Nonparametric End-to-End Probabilistic Forecasting of Distributed Generation Outputs with Missing Data Imputation
