5 citations · 7 across the 4 of their papers we have counts for
5 papers
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup +18
Transfer learning and meta-learning offer some of the most promising avenues to unlock the scalability of healthcare and consumer technologies driven by biosignal data. This is bec…
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition
Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas +5
Building subject-independent deep learning models for EEG decoding faces the challenge of strong covariate-shift across different datasets, subjects and recording sessions. Our app…
A Tutorial on Graph Theory for Brain Signal Analysis
Nikolaos Laskaris, Dimitrios A. Adamos, Anastasios Bezerianos
This tutorial paper refers to the use of graph-theoretic concepts for analyzing brain signals. For didactic purposes it splits into two parts: theory and application. In the first…
Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening
Dimitrios A. Adamos, Nikolaos Laskaris, Sifis Micheloyannis
Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perceptio…
Musical NeuroPicks: a consumer-grade BCI for on-demand music streaming services
Fotis Kalaganis, Dimitrios A. Adamos, Nikos Laskaris
We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener's subjective experience of music int…