Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series

no code implementations • 24 Oct 2023 • Alexandros-Menelaos Tzortzis, Sotiris Pelekis, Evangelos Spiliotis, Spiros Mouzakitis, John Psarras, Dimitris Askounis

Short-term load forecasting (STLF) is crucial for the daily operation of power grids.

Clustering Load Forecasting +2

In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance

no code implementations • 25 Feb 2023 • Sotiris Pelekis, Evangelos Karakolis, Francisco Silva, Vasileios Schoinas, Spiros Mouzakitis, Georgios Kormpakis, Nuno Amaro, John Psarras

In power grids, short-term load forecasting (STLF) is crucial as it contributes to the optimization of their reliability, emissions, and costs, while it enables the participation of energy companies in the energy market.

Load Forecasting Out-of-Distribution Generalization +2

A Multimodal Approach for Dementia Detection from Spontaneous Speech with Tensor Fusion Layer

no code implementations • 8 Nov 2022 • Loukas Ilias, Dimitris Askounis, John Psarras

However, existing state-of-the-art works proposing multimodal approaches do not take into consideration the inter- and intra-modal interactions and propose early and late fusion approaches.

Detecting Dementia from Speech and Transcripts using Transformers

no code implementations • 27 Oct 2021 • Loukas Ilias, Dimitris Askounis, John Psarras

Concurrently, little work has been done in terms of both the usage of transformer networks and the way the two modalities, i. e., speech and transcripts, are combined in a single neural network.

Electroencephalogram (EEG)