Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
Supervised Deep Multimodal Matrix Factorization (SD3MF), an interpretable framework for integrative brain network analysis that generalizes Symmetric Nonnegative Matrix Tri-Factorization from unsupervised single-graph clustering to supervised prediction over populations of multimodal graphs, is presented.