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Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data

arXiv (Cornell University)(2020)10.1109/bigdata50022.2020.9378462Source: DataRank Database

Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data is a research paper published in arXiv (Cornell University) (2020). On theSindex it has a DataRank of 0.

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Scored on demand from live citation data

Open Access0 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 0.00)OA: greenTopics (31)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Frederick Campbell ORCID,Andersen Chang ORCID,John F. Magnotti ORCID,Michael S. Beauchamp ORCID,Genevera I. Allen

Live enrichment

PubMed:19767382 OpenAlex:https://openalex.org/W3100278429

National Institutes of Health

Grant: 2R01NS065395-07A1

NEURAL SUBSTRATES OF OPTIMAL MULTISENSORY INTEGRATION

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

FWCI

0.00

Citation Percentile

0.1%

greenLicense: IEEE Copyright

repositoryhttps://arxiv.org/pdf/2011.09447

publisherhttp://xplorestaging.ieee.org/ielx7/9377717/9377728/09378462.pdf?arnumber=9378462

repositoryhttp://arxiv.org/abs/2011.09447

https://doi.org/10.1109/bigdata50022.2020.9378462

Fields of Study

Tensor decomposition and applicationsBlind Source Separation TechniquesSparse and Compressive Sensing Techniques02 engineering and technology03 medical and health sciences0302 clinical medicine0202 electrical engineering, electronic engineering, information engineering

Keywords

ElectrocorticographyInterpretabilityComputer scienceDimensionality reductionVisualizationArtificial intelligencePattern recognition (psychology)Dimension (graph theory)Machine learningSpeech recognitionElectroencephalographyMathematicsNeuroscienceSignal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningFOS: Physical sciencesPhysics - Medical PhysicsStatistics - ApplicationsMachine Learning (cs.LG)FOS: Electrical engineering, electronic engineering, information engineeringApplications (stat.AP)Medical Physics (physics.med-ph)Electrical Engineering and Systems Science - Signal Processing

Sustainable Development Goals

SDG 0: Quality Education