Maria Tzelepi and Anastasios Tefas, “Forecasting day-ahead electric load demand on Greek Energy Market”, Thirteen IEEE International Conference on Information, Intelligence, Systems and Applications (IISA) 2022.
Eleftherios Kouloumpris, Athina Konstantinou, Stamatis Karlos, Grigorios Tsoumakas, Ioannis Vlahavas, “Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity”, 12th EETN Conference on Artificial Intelligence (SETN 2022)
Maria Tzelepi, Alkmini Sapountzaki, Nikitas Maragkos and Anastasios Tefas, “Online Self‑Distillation for Electric Load Demand Forecasting on Greek Energy Market”, PAnhellenic Conference on Electronics and Telecommunications (PACET), 2022.
George Emmanouilidis, Maria Tzelepi and Anastasios Tefas, “Short‑Term Electric Load Demand Forecasting on Greek Energy Market using Deep Learning: A comparative study”, PAnhellenic Conference on Electronics and Telecommunications (PACET), 2022.
Achilleas Andronikos, Maria Tzelepi and Anastasios Tefas, “Residual Error Learning for Electricity Demand Forecasting”, International Conference on Engineering Applications of Neural Networks (EANN), 2023.
Charalampos Symeonidis and Nikos Nikolaidis, “Wind Energy Prediction Guided by Multiple-Location Weather Forecasts”, International Conference on Engineering Applications of Neural Networks (EANN), 2023.
Maria Tzelepi, Paraskevi Nousi and Anastasios Tefas, “Improving Electric Load Demand Forecasting with Anchor-based Forecasting Method”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
Paraskevi Nousi, Maria Tzelepi and Anastasios Tefas, “Anchored Input-Output Learning for Electrical Load Demand Forecasting”, IEEE International Symposium on Circuits and Systems (ISCAS), 2023.
Maria Tzelepi, Charalampos Symeonidis, Paraskevi Nousi, Efstratios Kakaletsis,Theodoros Manousis, Pavlos Tosidis, Nikos Nikolaidis, Anastasios Tefas, “Deep Learning for Energy Time-Series Analysis and Forecasting”, arxiv.
