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Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence(2021)10.1109/tpami.2021.3076155Source: DataRank Database

Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning is a research paper published in IEEE Transactions on Pattern Analysis and Machine Intelligence (2021). On theSindex it has a DataRank of 0. It has been cited 77 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access77 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (21 grants)OA: hybridTopics (47)IDs (PubMed)

FAIR Checklist

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Shenda Hong ORCID,Bruno Brandoli Machado ORCID,Stan Matwin ORCID,José F. Rodrigues ORCID,Jimeng Sun ORCID

Live enrichment

PubMed:19767382

Conselho Nacional de Desenvolvimento Cientfico e Tecnolgico

Grant: 167967/2017-7

Conselho Nacional de Desenvolvimento Cientfico e Tecnolgico

Grant: 305580/2017-5

Conselho Nacional de Desenvolvimento Cientfico e Tecnolgico

Grant: 406550/2018-2

National Science Foundation

Grant: CCF-1533768

National Science Foundation

Grant: IIS-1418511

National Science Foundation

Grant: IIS-1838042

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2014/25337-0

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2016/17078-0

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2017/08376-0

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2018/17620-5

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2019/04461-9

Fundao de Amparo Pesquisa do Estado de So Paulo

Grant: 2020/07200-9

National Institute of Health

Grant: NIH R01 1R01NS107291-01

National Institute of Health

Grant: R56HL138415

National Science Foundation

Grant: 1533768

XPS: FULL: DSD: A Parallel Tensor Infrastructure (ParTI!) for Data Analysis

National Science Foundation

Grant: 1838042

BigData:IA:Collaborative Research: TIMES: A tensor factorization platform for spatio-temporal data

National Institutes of Health

Grant: 1R01NS107291-01

Big Data and Deep Learning for the Interictal-Ictal-Injury Continuum

National Science Foundation

Grant: 2028839

Collaborative Research: PPoSS: Planning: Integrated Scalable Platform for Privacy-aware Collaborative Learning and Inference

National Institutes of Health

Grant: 1R56HL138415-01

Interpretable Deep Learning Model for Longitudinal Electronic Health Records and Applications to Heart Failure Prediction

National Science Foundation

Grant: 1418511

SCH: INT: Collaborative Research: High-throughput Phenotyping on Electronic Health Records using Multi-Tensor Factorization

National Science Foundation

Grant: 2014438

SCH:INT: Collaborative Research: Deep Sense: Interpretable Deep Learning for Zero-effort Phenotype Sensing and Its Application to Sleep Medicine

hybridLicense: cc-by

publisherhttps://ieeexplore.ieee.org/ielx7/34/9893109/09416768.pdf

publisherhttps://ieeexplore.ieee.org/ielam/34/9893109/9416768-aam.pdf

publisherhttp://xplorestaging.ieee.org/ielx7/34/9893109/09416768.pdf?arnumber=9416768

repositoryhttps://arxiv.org/pdf/2008.12833

repositoryhttps://doi.org/10.1109/TPAMI.2021.3076155

Fields of Study

02 engineering and technology0202 electrical engineering, electronic engineering, information engineering

Keywords

I.2FOS: Computer and information sciencesArtificial neural networkComputer Science - Machine LearningArtificial intelligenceTime seriesI.5Computer Science - Artificial IntelligenceElectricity Price and Load Forecasting Methods37M10, 68T07, 68T05, 68T37, 82C32Recurrent neural networkSocial SciencesMachine Learning (stat.ML)Management Science and Operations ResearchClustering of Time Series Data and AlgorithmsGraphMachine Learning (cs.LG)Decision SciencesForecasting ModelsEngineeringDeep LearningTheoretical computer scienceStatistics - Machine LearningMachine learningFOS: Electrical engineering, electronic engineering, information engineeringSeries (stratigraphy)Pattern DiscoveryNeural and Evolutionary Computing (cs.NE)I.2; I.5; I.2.4; I.2.6; I.5.1Electrical and Electronic EngineeringTime Series AnalysisBiologyHyperparameterI.2.4I.5.1Time Series ForecastingI.2.6Computer Science - Neural and Evolutionary ComputingPaleontologyPredicting Stock Market Trends and MovementsComputer scienceMultivariate statisticsArtificial Intelligence (cs.AI)Signal ProcessingPhysical Sciences