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cs.LG2022★ 7 cited
Deep Representations for Time-varying Brain Datasets
Sikun Lin, Shuyun Tang, Scott Grafton +1
Finding an appropriate representation of dynamic activities in the brain is crucial for many downstream applications. Due to its highly dynamic nature, temporally averaged fMRI (fu…
cs.LG2017★ 2 cited
Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case
Konstantinos Slavakis, Shiva Salsabilian, David S. Wack +5
This paper advocates Riemannian multi-manifold modeling in the context of network-wide non-stationary time-series analysis. Time-series data, collected sequentially over time and a…