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Learning Networks From Wide-Sense Stationary Stochastic Processes

IEEE Transactions on Signal and Information Processing over Networks(2025)10.1109/tsipn.2025.3583488Source: DataRank Database

Learning Networks From Wide-Sense Stationary Stochastic Processes is a research paper published in IEEE Transactions on Signal and Information Processing over Networks (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

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Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 2.25)OA: greenTopics (29)IDs (PubMed, PMC, OpenAlex)

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 (5)

Jiajun Cheng ORCID,Rajasekhar Anguluri ORCID,Deepjyoti Deka ORCID,Gautam Dasarathy ORCID,Anirudh Rayas

Live enrichment

PubMed:41180157 PMC:PMC12574584 OpenAlex:https://openalex.org/W4411866968

High-Performance Artificial Intelligence

Grant: 20230771DI

National Science Foundation

Grant: CCF-2048223

National Institutes of Health

Grant: 1R01GM140468-01

Graphical Models from Partially Observed Interactions with Biomedical Applications

NIGMS NIH HHS

Grant: R01 GM140468

National Science Foundation

Grant: 2048223

CAREER: Learning and Leveraging the Structure of Large Graphs: Novel Theory and Algorithms

LANL’s Directed Research and Development

FWCI

2.25

Citation Percentile

0.9%

Citation Trend

2026

greenLicense: IEEE Copyright

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12574584/

GREENhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12574584/

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12574584/

publisherhttps://ieeexplore.ieee.org/ielam/6884276/10789318/11060910-aam.pdf

publisherhttp://xplorestaging.ieee.org/ielx8/6884276/10789318/11060910.pdf?arnumber=11060910

Fields of Study

Neural Networks and ApplicationsBayesian Modeling and Causal InferenceGaussian Processes and Bayesian InferenceMathematicsComputer ScienceEngineeringMedicine0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Sense (electronics)Computer scienceCognitive sciencePsychologyChemistryConservation LawsNetwork Topology InferenceSpectral Precision Matrixℓ1-regularized Whittle’s Likelihood EstimatorMachine LearningSignal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningStatistics - Machine LearningSignal ProcessingFOS: Electrical engineering, electronic engineering, information engineeringMachine Learning (stat.ML)Electrical Engineering and Systems Science - Signal ProcessingArticleMachine Learning (cs.LG)