Fast Sequential Clustering in Riemannian Manifolds for Dynamic and Time-Series-Annotated Multilayer Networks

Fast Sequential Clustering in Riemannian Manifolds for Dynamic and Time-Series-Annotated Multilayer Networks

This work exploits Riemannian manifolds to build a sequential-clustering framework able to address a wide variety of clustering tasks in dynamic multilayer (brain) networks via the information extracted from their nodal time-series. The discussion follows a bottom-up path, starting from feature extr...

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Bibliographic Details
Main Authors: Cong Ye, Konstantinos Slavakis, Johan Nakuci, Sarah F. Muldoon, John Medaglia
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Clustering
multilayer
network
Riemannian manifold
sequential
time-series
Online Access:https://ieeexplore.ieee.org/document/9321498/

Internet

https://ieeexplore.ieee.org/document/9321498/

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