3 papers
cs.LG2025
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, Mohammad H. Abbasi +3
Confounders are extraneous variables that affect both the input and the target, resulting in spurious correlations and biased predictions. There are recent advances in dealing with…
eess.IV2024
Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging
Magdalini Paschali, Yu Hang Jiang, Spencer Siegel +4
Recent advancements in medicine have confirmed that brain disorders often comprise multiple subtypes of mechanisms, developmental trajectories, or severity levels. Such heterogenei…
cs.CV2024
SpaRG: Sparsely Reconstructed Graphs for Generalizable fMRI Analysis
Camila González, Yanis Miraoui, Yiran Fan +2
Deep learning can help uncover patterns in resting-state functional Magnetic Resonance Imaging (rs-fMRI) associated with psychiatric disorders and personal traits. Yet the problem…