Latest

• Identifying Good Donor Datasets for Transfer Learning Scenarios in Motor Imagery BCI
• Review of Deep Representation Learning Techniques for Brain-Computer Interfaces
• Approximate UMAP allows for high-rate online visualization of high-dimensional data streams
• S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention
• Synthesizing EEG Signals from Event-Related Potential Paradigms with Conditional Diffusion Models
• Review of Deep Representation Learning Techniques for BCI
• Bringing deep learning decoding models to the lab
• Generative Models
• Approximate UMAP
• Transfer Learning between Motor Imagery Datasets Using Deep Learning - Validation of Framework and Comparison of Datasets
• Neural network transfer learning with fast calibration for mental imagery decoding
• Pre-trained motor-imagery models
• An Embedding for EEG Signals Learned Using a Triplet Loss
• New article on embedding learning for BCI
• Learning to repair artifacts in brain signals
• Embedding Neurophysiological Signals
• Best poster prize won!
• Deep representation learning