Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale

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Data management plan for the grant, "Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale." This project aims to improve the computation efficiency of graph neural networks (GNNs), which are an emerging class of deep learning models on graphs, with many successful applications, such as, recommendation systems, drug discovery, social network analysis, and code vulnerability detection. This project aims to to design an efficient GNN framework via algorithm and system co-design for both static and dynamic graphs.

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Ji, Yuede 2024-01-01/2026-12-31.

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This text is part of the collection entitled: UNT Funded Research Projects and was provided by the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 56 times, with 28 in the last month. More information about this text can be viewed below.

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  • Ji, Yuede Principal Investigator, University of North Texas

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UNT College of Engineering

The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.

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Data management plan for the grant, "Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale." This project aims to improve the computation efficiency of graph neural networks (GNNs), which are an emerging class of deep learning models on graphs, with many successful applications, such as, recommendation systems, drug discovery, social network analysis, and code vulnerability detection. This project aims to to design an efficient GNN framework via algorithm and system co-design for both static and dynamic graphs.

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  • Grant Number: 2331301
  • Grant Number: GFP0000211
  • Grant Number: GAWD000316
  • Archival Resource Key: ark:/67531/metadc2155434

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UNT Funded Research Projects

Records for grants awarded to researchers at the University of North Texas. These records establish unique identifiers that are publicly accessible for these research projects. In most cases, the data management plan for the project has been deposited with the item. Each record has a link to a full bibliography of the research output including data and publications.

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  • 2024-01-01/2026-12-31

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  • Aug. 25, 2023, 12:58 p.m.

Description Last Updated

  • Sept. 20, 2023, 1:35 p.m.

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Ji, Yuede. Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale, text, 2024-01-01/2026-12-31; (https://digital.library.unt.edu/ark:/67531/metadc2155434/: accessed May 26, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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