SD3MF learns deep hierarchical factorizations of multimodal brain graphs with a shared latent space and encoder-decoder training to jointly reconstruct graphs and predict supervised outcomes.
Correspondence of the brain’s functional architecture during activation and rest.Proceedings of the National Academy of Sciences, 106(31):13040–13045, 2009
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Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
SD3MF learns deep hierarchical factorizations of multimodal brain graphs with a shared latent space and encoder-decoder training to jointly reconstruct graphs and predict supervised outcomes.