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MetaNO: How to transfer your knowledge on learning hidden physics

Computer Methods in Applied Mechanics and Engineering(2023)10.1016/j.cma.2023.116280Source: DataRank Database

MetaNO: How to transfer your knowledge on learning hidden physics is a research paper published in Computer Methods in Applied Mechanics and Engineering (2023). On theSindex it has a DataRank of 0. It has been cited 9 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access9 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 1.15)OA: greenTopics (35)IDs (PubMed, PMC, OpenAlex)Annotations (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)

Huaiqian You ORCID,Tian Gao ORCID,Mo Yu ORCID,Chung‐Hao Lee ORCID,Yue Yu ORCID

Live enrichment

PubMed:38292246 PMC:PMC10824406 OpenAlex:https://openalex.org/W4385335847

NHLBI NIH HHS

Grant: R01 HL159475

National Science Foundation

Grant: 2019035

CC* Compute: Acquisition of a Lehigh University HPC cluster to enhance collaboration, research productivity and educational impact

National Institutes of Health

Grant: 1R01HL159475-01A1

Improving outcomes in endovascular treatment of intracranial aneurysms: Combining additive manufacturing, in-silico modeling, and shape memory polymers

National Science Foundation

Grant: 1753031

CAREER: A Local-Nonlocal Coupling Framework for Tissue Damage in Fluid-Structure Interaction

FWCI

1.15

Citation Percentile

0.8%

Citation Trend

2023

2024

2025

2026

greenLicense: Elsevier TDM

repositoryhttps://escholarship.org/content/qt25q1h70n/qt25q1h70n.pdf

publisherhttps://api.elsevier.com/content/article/PII:S0045782523004048?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0045782523004048?httpAccept=text/plain

repositoryhttps://escholarship.org/uc/item/25q1h70n

Fields of Study

Model Reduction and Neural NetworksDomain Adaptation and Few-Shot LearningMachine Learning in Materials Science02 engineering and technology01 natural sciences0103 physical sciences0202 electrical engineering, electronic engineering, information engineering0210 nano-technology

Keywords

Operator (biology)Field (mathematics)Partial differential equationComputer scienceArtificial intelligenceTransfer of learningArtificial neural networkMachine learningAlgorithmMathematicsMathematical analysisMeta-learningTransfer LearningScientific Machine LearningNeural OperatorsData-driven Physics ModelingOperator-regression Neural NetworksFOS: Computer and information sciencesComputer Science - Machine Learning510Machine Learning (cs.LG)Numerical and other methods in solid mechanicsFOS: MathematicsMathematics - Numerical AnalysisArtificial neural networks and deep learning000Numerical Analysis (math.NA)