Impact of Clustering Methods on Machine Learning-based Solar Power Prediction Models. - Phil Aupke; Andreas Kassler; Andreas D. Theocharis; Magnus Nilsson; Isac Myrén Andersson (ISC2, 2022)

DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks. - Firas Bayram; Phil Aupke; Bestoun S. Ahmed; Andreas Kassler; Andreas D. Theocharis; Jonas Forsman (Eng. Appl. Artif. Intell., 2023)

Uncertainty-Aware Forecasting of Computational Load in MECs Using Distributed Machine Learning: A Tokyo Case Study. - Phil Aupke; Akihiro Nakao; Andreas Kassler (ICCCN, 2024)