A tri-view information-bottleneck model that fuses pairwise, triadic and tetradic O-information outperforms eleven baselines on four fMRI psychiatric datasets while revealing region-level synergy-redundancy patterns.
Pime: Prototype-based interpretable mcts-enhanced brain network analysis for disorder diagnosis
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
CORE decouples site confounders in fMRI networks, profiles transient dynamics on a population scaffold using line graphs, and applies subject-adaptive gating to achieve up to 6.7% better cross-site generalization on ABIDE, REST-meta-MDD, SRPBS, and ABCD datasets.
citing papers explorer
-
Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis
A tri-view information-bottleneck model that fuses pairwise, triadic and tetradic O-information outperforms eleven baselines on four fMRI psychiatric datasets while revealing region-level synergy-redundancy patterns.
-
When Brain Networks Travel: Learning Beyond Site
CORE decouples site confounders in fMRI networks, profiles transient dynamics on a population scaffold using line graphs, and applies subject-adaptive gating to achieve up to 6.7% better cross-site generalization on ABIDE, REST-meta-MDD, SRPBS, and ABCD datasets.