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

(2020)10.36227/techrxiv.12725369Source: DataRank Database

Fast Sequential Clustering in Riemannian Manifolds for Dynamic and Time-Series-Annotated Multilayer Networks is a research paper (2020). On theSindex it has a DataRank of 0.

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Enrichment:Funding (5 grants)OA: goldTopics (27)IDs (PubMed, OpenAlex)

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Authors (5)

Konstantinos Slavakis ORCID,Johan Nakuci ORCID,Sarah F. Muldoon ORCID,John D. Medaglia ORCID,Cong Ye ORCID

Live enrichment

PubMed:23304386 OpenAlex:https://openalex.org/W4235138536

National Institutes of Health

Grant: 5P41EB015896-18

Center for Functional Imaging Technologies

National Institutes of Health

Grant: 1S10RR023401-01A2

A Storage Area Network for Structural and Functional Image Analysis

National Institutes of Health

Grant: 5U01MH093765-02

The Human Connectome Project (HCP)

National Institutes of Health

Grant: 1S10RR019307-01

Computeserver Structural &Functional Image Analysis

National Institutes of Health

Grant: 1S10RR023043-01

SILICON GRAPHICS PRISM EXTREME 128P/1TB

goldLicense: cc-by

https://doi.org/10.36227/techrxiv.12725369

https://doi.org/10.1109/ojsp.2021.3051453

https://ieeexplore.ieee.org/ielx7/8782710/9336068/09321498.pdf

https://doi.org/10.36227/techrxiv.12725369.v1

Fields of Study

Functional Brain Connectivity StudiesMental Health Research TopicsTopological and Geometric Data Analysis03 medical and health sciences0302 clinical medicine

Keywords

Cluster analysisRiemannian geometryRiemannian manifoldComputer scienceArtificial intelligencePattern recognition (psychology)MathematicsKernel (algebra)Statistical manifoldAlgorithmTopology (electrical circuits)Information geometryMathematical analysisGeometryPure mathematicsmultilayertime-seriesnetworkElectrical engineering. Electronics. Nuclear engineeringsequentialClusteringTK1-9971