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PrOuD: Probabilistic Outlier Detection Solution for Time Series Analysis on Real-world Photovoltaic Inverters, , , and . Energies (MDPI), 17 (1): 64 (2024)Quantile Surfaces -- Generalizing Quantile Regression to Multivariate Targets, , , , and . arXiv e-prints, (2020)Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle, , and . Meteorologische Zeitschrift, 26 (3): 319--331 (2017)Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast., , and . CoRR, (2022)Deep Learning Based Failure Prediction in Wind Turbines Using SCADA Data, , , and . Conference for Wind Power Drives (CWD), page 391--404. (2019)Evaluation of Anomaly Detection of an Autoencoder Based on Maintenace Information and Scada-Data, , , , , , , and . Energies, 13 (5): 1063 (2020)Uncertainty and Utility Sampling with Pre-Clustering., , , and . IAL@PKDD/ECML, volume 3079 of CEUR Workshop Proceedings, page 21-34. CEUR-WS.org, (2021)Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting., , and . ICMLA, page 1530-1536. IEEE, (2022)Targeted adversarial attacks on wind power forecasts., , , and . Mach. Learn., 113 (2): 863-889 (February 2024)Statistical correction scheme for the wind power allocation to transformer stations in the transmission grid, , and . Electric Power Systems Research, (2020)