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11th International Symposium on Medical Information Processing and Analysis
In the present work we study a family of generative network model and its applications for modeling the human connectome. We introduce a minor but novel variant of the Mixed Membership Stochastic Blockmodel and apply it and two other related model to two human connectome datasets (ADNI and a Bipolar Disorder dataset) with both control and diseased subjects. We further provide a simple generative classifier that, alongside more discriminating methods, provides evidence that blockmodelsdoi:10.1117/12.2211519 fatcat:tpttoovxuzcnrhmfbirztsp7qi