no code implementations • 22 Dec 2021 • Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
In order to understand the connection between stimuli of interest and brain activity, and analyze differences and commonalities between subjects, it becomes important to learn a meaningful embedding of the data that denoises, and reveals its intrinsic structure.
no code implementations • 2 Nov 2018 • Guixiang Ma, Nesreen K. Ahmed, Ted Willke, Dipanjan Sengupta, Michael W. Cole, Nicholas B. Turk-Browne, Philip S. Yu
We propose an end-to-end similarity learning framework called Higher-order Siamese GCN for multi-subject fMRI data analysis.