18 citations · 42 across the 15 of their papers we have counts for
4 papers · 1 filter
A deep learning model for data-driven discovery of functional connectivity
Usman Mahmood, Zening Fu, Vince Calhoun +1
Functional connectivity (FC) studies have demonstrated the overarching value of studying the brain and its disorders through the undirected weighted graph of fMRI correlation matri…
Multi network InfoMax: A pre-training method involving graph convolutional networks
Usman Mahmood, Zening Fu, Vince Calhoun +1
Discovering distinct features and their relations from data can help us uncover valuable knowledge crucial for various tasks, e.g., classification. In neuroimaging, these features…
Brain dynamics via Cumulative Auto-Regressive Self-Attention
Usman Mahmood, Zening Fu, Vince Calhoun +1
Multivariate dynamical processes can often be intuitively described by a weighted connectivity graph between components representing each individual time-series. Even a simple repr…
Fusing multimodal neuroimaging data with a variational autoencoder
Eloy Geenjaar, Noah Lewis, Zening Fu +3
Neuroimaging studies often involve the collection of multiple data modalities. These modalities contain both shared and mutually exclusive information about the brain. This work ai…