3 papers
cs.LG2026
NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
Konstantinos Kontras, Trui Osselaer, Stylianos G. Mouslech +12
Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including electroencephalography (EEG),…
cs.LG2026
SynIB: Informational Bottleneck for Maximizing Synergy in Multimodal Learning
Konstantinos Kontras, Teodora Gagaleska, Thomas Strypsteen +4
A central objective in multimodal learning is to capture synergy: task-relevant information that arises only from the joint use of multiple modalities, and is not available from an…
cs.LG2025
Balancing Multimodal Training Through Game-Theoretic Regularization
Konstantinos Kontras, Thomas Strypsteen, Christos Chatzichristos +3
Multimodal learning holds promise for richer information extraction by capturing dependencies across data sources. Yet, current training methods often underperform due to modality…