Model: Facebook AI Research - FAIR-NRAR

    Name: NRAR
    Abbreviation: FAIR-NRAR
    Owner: covid19hub
    Team name: Facebook AI Research
    Description: Neural Relational Autoregressive Model
    Contributors: Matthew Le, Mark Ibrahim, Levent Sagun, Timothee Lacroix, Maximilian Nickel <maxn@fb.com>
    License: Creative Commons Attribution Non-Commercial 4.0
    Notes: primary
    Citation: https://ai.facebook.com/research/publications/neural-relational-autoregression-for-high-resolution-covid-19-forecasting/
    Methods: We combine recurrent neural networks with a vector autoregressive model and train the joint model with a specific regularization scheme that increases the coupling between regions. This approach is akin to using Granger causality as a relational inductive bias and helps training of high-resolution models by borrowing statistical strength across regions.
    Home: https://dataforgood.fb.com/tools/covid-19-forecasts/
    Auxiliary data: Missing

    Forecasts (4)

    Timezero Data Source Upload Time Issue date Version
    2020-11-24 2020-11-24-FAIR-NRAR.csv 2020-11-25 18:19:25 UTC 2020-11-25
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    2020-11-22 2020-11-22-FAIR-NRAR.csv 2020-11-23 18:22:24 UTC 2020-11-23
    2020-11-19 2020-11-19-FAIR-NRAR.csv 2020-11-24 01:00:46 UTC 2020-11-23
    2020-11-18 2020-11-18-FAIR-NRAR.csv 2020-11-24 01:01:18 UTC 2020-11-23
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