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    • ARC Code TI: Block-GP: Scalable Gaussian Process Regression

    Metadata Updated: December 7, 2023

    Block GP is a Gaussian Process regression framework for multimodal data, that can be an order of magnitude more scalable than existing state-of-the-art nonlinear regression algorithms. The framework builds local Gaussian Processes on semantically meaningful partitions of the data and provides higher prediction accuracy than a single global model with very high confidence.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date December 7, 2023
    Data Update Frequency irregular

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date December 7, 2023
    Publisher Ames Research Center
    Maintainer
    Identifier OCIO-Fitara-113
    Data First Published 2015-07-21
    Data Last Modified 2020-01-29
    Category Management/Operations
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://data.nasa.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 6b803623-fa71-460b-ae6a-3fc87f254ca7
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL http://ti.arc.nasa.gov/opensource/projects/block-gp/
    Program Code 026:046
    Source Datajson Identifier True
    Source Hash e52b00923df994e907a71f45b8439cc5d2c7a1675533a20149a7eb2ca1e1ad7b
    Source Schema Version 1.1

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