4 citations · 11 across the 6 of their papers we have counts for
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cs.AI2022★ 4 cited
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…
stat.ML2022
Physics-informed neural networks for pathloss prediction
Steffen Limmer, Alberto Martinez Alba, Nicola Michailow
This paper introduces a physics-informed machine learning approach for pathloss prediction. This is achieved by including in the training phase simultaneously (i) physical dependen…