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Neural Stein Critics With Staged L 2-Regularization

IEEE Transactions on Information Theory(2023)10.1109/tit.2023.3299258Source: DataRank Database

Neural Stein Critics With Staged L 2-Regularization is a research paper published in IEEE Transactions on Information Theory (2023). On theSindex it has a DataRank of 0. It has been cited 2 times.

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2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (14 grants)Topics (10)

FAIR Checklist

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Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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Authors (3)

Xiuyuan Cheng ORCID,Yao Xie ORCID,Matthew Repasky

Live enrichment

NSF

Grant: DMS-2134037

NSF CAREER

Grant: CCF-1650913

NSF

Grant: CMMI-2015787

NSF

Grant: CMMI-2112533

NSF

Grant: DMS-1938106

NSF

Grant: DMS-1830210

NSF

Grant: DMS-1818945

NIH

Grant: R01GM131642

National Science Foundation

Grant: 1818945

Collaborative Research: Geometric Analysis and Computation for Generative Models

National Science Foundation

Grant: 2134037

Bridging Statistical Hypothesis Tests and Deep Learning for Reliability and Computational Efficiency

National Science Foundation

Grant: 1938106

Sequential Detection and Prediction for Solar Situation Awareness in Power Networks

National Science Foundation

Grant: 1830210

ATD: Scanning Dynamic Spatial-Temporal Discrete Events for Threat Detection

National Institutes of Health

Grant: 5R01GM131642-04

EFFICIENT METHODS FOR CALIBRATION, CLUSTERING, VISUALIZATION AND IMPUTATION OF LARGE scRNA-seq DATA

National Science Foundation

Grant: 2015787

Data-Driven Optimal Police Patrol Zone Districting and Staffing

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

FOS: Computer and information sciencesComputer Science - Machine LearningStatistics - Machine LearningFOS: MathematicsMathematics - Statistics TheoryMachine Learning (stat.ML)Statistics Theory (math.ST)Machine Learning (cs.LG)