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20212023
most citedCalibration of Transformer-based Models for Identifying Stress and Depression in Social Media

97 citations · 447 across the 15 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

cs.LG2023★ 23 cited

Data-driven building energy efficiency prediction using physics-informed neural networks

Vasilis Michalakopoulos, Sotiris Pelekis, Giorgos Kormpakis +3

The analytical prediction of building energy performance in residential buildings based on the heat losses of its individual envelope components is a challenging task. It is worth…

cs.LG2023★ 2 cited

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

Alexandros-Menelaos Tzortzis, Sotiris Pelekis, Evangelos Spiliotis +3

Short-term load forecasting (STLF) is crucial for the daily operation of power grids. However, the non-linearity, non-stationarity, and randomness characterizing electricity demand…

cs.CL2023★ 16 cited

Multimodal Detection of Bots on X (Twitter) using Transformers

Loukas Ilias, Ioannis Michail Kazelidis, Dimitris Askounis

Although not all bots are malicious, the vast majority of them are responsible for spreading misinformation and manipulating the public opinion about several issues, i.e., election…

cs.LG2023★ 20 cited

DeepTSF: Codeless machine learning operations for time series forecasting

Sotiris Pelekis, Evangelos Karakolis, Theodosios Pountridis +4

This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless model…

cs.CL2023★ 20 cited

Multitask learning for recognizing stress and depression in social media

Loukas Ilias, Dimitris Askounis

Stress and depression are prevalent nowadays across people of all ages due to the quick paces of life. People use social media to express their feelings. Thus, social media constit…

cs.CL2023★ 97 cited

Calibration of Transformer-based Models for Identifying Stress and Depression in Social Media

Loukas Ilias, Spiros Mouzakitis, Dimitris Askounis

In today's fast-paced world, the rates of stress and depression present a surge. Social media provide assistance for the early detection of mental health conditions. Existing metho…

cs.CL2023★ 24 cited

Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech

Loukas Ilias, Dimitris Askounis

Alzheimer's disease (AD) constitutes a complex neurocognitive disease and is the main cause of dementia. Although many studies have been proposed targeting at diagnosing dementia t…

cs.LG2023★ 53 cited

Targeted demand response for flexible energy communities using clustering techniques

Sotiris Pelekis, Angelos Pipergias, Evangelos Karakolis +4

The present study proposes clustering techniques for designing demand response (DR) programs for commercial and residential prosumers. The goal is to alter the consumption behavior…

cs.LG2023★ 33 cited

A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

Sotiris Pelekis, Ioannis-Konstantinos Seisopoulos, Evangelos Spiliotis +4

Short-term load forecasting (STLF) is vital for the effective and economic operation of power grids and energy markets. However, the non-linearity and non-stationarity of electrici…

cs.LG2023★ 1 cited

Neural Architecture Search with Multimodal Fusion Methods for Diagnosing Dementia

Michail Chatzianastasis, Loukas Ilias, Dimitris Askounis +1

Alzheimer's dementia (AD) affects memory, thinking, and language, deteriorating person's life. An early diagnosis is very important as it enables the person to receive medical help…