Brain-Computer Interfaces Comparison Hub
3 papers - avg viability 6.7
Top Papers
- BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding(8.0)
BrainStack offers a novel neuro-inspired framework for EEG-based language decoding, outperforming state-of-the-art models.
- SENSE: Efficient EEG-to-Text via Privacy-Preserving Semantic Retrieval(7.0)
SENSE is a lightweight EEG-to-text framework that ensures privacy while translating brain activity into natural language.
- SHINE: Sequential Hierarchical Integration Network for EEG and MEG(5.0)
Develop a neural network model, SHINE, for reconstructing speech-sequence data from MEG signals.