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Subbotin Graphical Models for Extreme Value Dependencies with Applications to Functional Neuronal Connectivity

arXiv (Cornell University)(2021)10.48550/arxiv.2106.11554Source: DataRank Database

Subbotin Graphical Models for Extreme Value Dependencies with Applications to Functional Neuronal Connectivity is a research paper published in arXiv (Cornell University) (2021). On theSindex it has a DataRank of 0.

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Enrichment:Funding (2 grants)OA: greenTopics (31)IDs (PubMed, OpenAlex)

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Authors (2)

Genevera I. Allen,Andersen Chang ORCID

Live enrichment

PubMed:19276002 OpenAlex:https://openalex.org/W4293566020

National Science Foundation

Grant: 1707400

NeuroNex Theory Team: Inferring interactions between neurons, stimuli, and behavior

National Institutes of Health

Grant: 5R01GM140468-02

Graphical Models from Partially Observed Interactions with Biomedical Applications

greenLicense: cc-by

repositoryhttps://arxiv.org/pdf/2106.11554

repositoryhttp://arxiv.org/abs/2106.11554

repositoryhttps://doi.org/10.48550/arxiv.2106.11554

https://doi.org/10.1214/22-aoas1723

https://dx.doi.org/10.48550/arxiv.2106.11554

Fields of Study

Functional Brain Connectivity StudiesNeural dynamics and brain functionMachine Learning in Materials ScienceMethodology (stat.ME)FOS: Computer and information sciences62H2201 natural sciences03 medical and health sciences0302 clinical medicine0101 mathematics

Keywords

Graphical modelComputer scienceThresholdingCalcium imagingDependency (UML)Artificial intelligenceExtreme value theoryData miningMachine learningMathematicsImage (mathematics)FOS: Computer and information sciencesexponential family graphical modelsextreme valuesApplications of statisticsMethodology (stat.ME)Subbotin distributiongraphical modelsgeneralized normal distribution62H22Statistics - Methodology