3 papers
cs.LG2026
Riemannian Geometry-Preserving Variational Autoencoder for MI-BCI Data Augmentation
Viktorija Poļaka, Ivo Pascal de Jong, Andreea Ioana Sburlea
This paper addresses the challenge of generating synthetic electroencephalogram (EEG) covariance matrices for motor imagery brain-computer interface (MI-BCI) applications. Objectiv…
cs.LG2026
The Challenge of Out-Of-Distribution Detection in Motor Imagery BCIs
Merlijn Quincent Mulder, Matias Valdenegro-Toro, Andreea Ioana Sburlea +1
Machine Learning classifiers used in Brain-Computer Interfaces make classifications based on the distribution of data they were trained on. When they need to make inferences on sam…
cs.CL2025
NLP Methods May Actually Be Better Than Professors at Estimating Question Difficulty
Leonidas Zotos, Ivo Pascal de Jong, Matias Valdenegro-Toro +3
Estimating the difficulty of exam questions is essential for developing good exams, but professors are not always good at this task. We compare various Large Language Model-based m…