32 citations · 59 across the 28 of their papers we have counts for
9 papers · 1 filter
BrainCodes: A Lightweight EEG Foundation Model over Discrete Neural Codes
Kleanthis Avramidis, Ivan Tashev, Dimitra Emmanouilidou
Recent electroencephalography (EEG) foundation models increasingly emphasize model scale, potentially limiting their deployment on resource-constrained devices and in everyday envi…
A Multi-dimensional Framework for Evaluating Generalization in EEG Foundation Models
Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +2
Evaluating foundation models under appropriate adaptation settings is essential for understanding the quality and transferability of the learned representations. Recent EEG foundat…
Aperiodic and Low-Frequency Spectral Bias in Reconstruction based EEG Foundation Models
Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +7
EEG foundation models, pre-trained on large-scale unlabelled EEG data, have emerged as a promising direction towards learning generalizable EEG representations. Despite showing pos…
Neural Codecs as Biosignal Tokenizers
Kleanthis Avramidis, Tiantian Feng, Woojae Jeong +4
Neurophysiological recordings such as electroencephalography (EEG) offer accessible and minimally invasive means of estimating physiological activity for applications in healthcare…
Neural Responses to Affective Sentences Reveal Signatures of Depression
Aditya Kommineni, Woojae Jeong, Kleanthis Avramidis +13
Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core fu…
Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements
Kleanthis Avramidis, Woojae Jeong, Aditya Kommineni +14
Identifying physiological and behavioral markers for mental health conditions is a longstanding challenge in psychiatry. Depression and suicidal ideation, in particular, lack objec…
Knowledge-guided EEG Representation Learning
Aditya Kommineni, Kleanthis Avramidis, Richard Leahy +1
Self-supervised learning has produced impressive results in multimedia domains of audio, vision and speech. This paradigm is equally, if not more, relevant for the domain of biosig…
Scaling Representation Learning from Ubiquitous ECG with State-Space Models
Kleanthis Avramidis, Dominika Kunc, Bartosz Perz +5
Ubiquitous sensing from wearable devices in the wild holds promise for enhancing human well-being, from diagnosing clinical conditions and measuring stress to building adaptive hea…
Augmentation Methods on Monophonic Audio for Instrument Classification in Polyphonic Music
Agelos Kratimenos, Kleanthis Avramidis, Christos Garoufis +2
Instrument classification is one of the fields in Music Information Retrieval (MIR) that has attracted a lot of research interest. However, the majority of that is dealing with mon…