9 papers
Disentangling Model and Human Data Uncertainty in Apparent Facial Age Estimation
Andrei Foitos, Ivo Pascal de Jong, Matias Valdenegro-Toro
Estimating the apparent age of individuals from facial images is challenging due to the subjective nature of perception and the inherent variability of the data. We investigate the…
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…
Why Large Language Models can Secretly Outperform Embedding Similarity in Information Retrieval
Matei Benescu, Ivo Pascal de Jong
With the emergence of Large Language Models (LLMs), new methods in Information Retrieval are available in which relevance is estimated directly through language understanding and r…
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…
Measuring Orthogonality as the Blind-Spot of Uncertainty Disentanglement
Ivo Pascal de Jong, Andreea Ioana Sburlea, Matthia Sabatelli +1
Aleatoric (data) and epistemic (knowledge) uncertainty are textbook components of Uncertainty Quantification. Jointly estimating these components has been shown to be problematic a…
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…