Data-Driven NeuroTechnology lab
Data-Driven NeuroTechnology lab
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Thibault Verhoeven
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Rethinking BCI paradigm and machine learning algorithm as a symbiosis: zero calibration, guaranteed convergence and high decoding performance
Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier]
Unsupervised learning for brain–computer interfaces based on event-related potentials
Improving zero-training brain-computer interfaces by mixing model estimators
Improving learning from label proportions by reducing the feature dimensionality
Learning from Label Proportions in BCI -- a Symbiotic Design for Stimulus Preservation and Signal Decoding
Learning from label proportions in brain-computer interfaces: online unsupervised learning with guarantees
Mixing two unsupervised estimators for event-related potential decoding: An online evaluation
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