Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Interpretable Cross-Network Attention for Resting-State fMRI Representation Learning
Karanpartap Singh, Adam Turnbull, Mohammad Abbasi +3
Understanding how large-scale functional brain networks reorganize during cognitive decline remains a central challenge in neuroimaging. While recent self-supervised models have sh…
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…
cs.LG2025
The Most Important Features in Generalized Additive Models Might Be Groups of Features
Tomas M. Bosschieter, Luis Franca, Jessica Wolk +8
While analyzing the importance of features has become ubiquitous in interpretable machine learning, the joint signal from a group of related features is sometimes overlooked or ina…