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eess.IV2020
Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint
Ahmed Nebli, Ugur Ali Kaplan, Islem Rekik
Learning how to predict the brain connectome (i.e. graph) development and aging is of paramount importance for charting the future of within-disorder and cross-disorder landscape o…
eess.IV2020
Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping
Ahmed Nebli, Islem Rekik
Brain connectivity networks, derived from magnetic resonance imaging (MRI), non-invasively quantify the relationship in function, structure, and morphology between two brain region…
eess.IV2020
Foreseeing Brain Graph Evolution Over Time Using Deep Adversarial Network Normalizer
Zeynep Gurler, Ahmed Nebli, Islem Rekik
Foreseeing the brain evolution as a complex highly inter-connected system, widely modeled as a graph, is crucial for mapping dynamic interactions between different anatomical regio…