3 papers
cs.LG2025
LearnAD: Learning Interpretable Rules for Brain Networks in Alzheimer's Disease Classification
Thomas Andrews, Mark Law, Sara Ahmadi-Abhari +1
We introduce LearnAD, a neuro-symbolic method for predicting Alzheimer's disease from brain magnetic resonance imaging data, learning fully interpretable rules. LearnAD applies sta…
cs.CV2023
Evaluating The Robustness of Self-Supervised Representations to Background/Foreground Removal
Xavier F. Cadet, Ranya Aloufi, Alain Miranville +2
Despite impressive empirical advances of SSL in solving various tasks, the problem of understanding and characterizing SSL representations learned from input data remains relativel…
cs.LG2022
FIB: A Method for Evaluation of Feature Impact Balance in Multi-Dimensional Data
Xavier F. Cadet, Sara Ahmadi-Abhari, Hamed Haddadi
Errors might not have the same consequences depending on the task at hand. Nevertheless, there is limited research investigating the impact of imbalance in the contribution of diff…