Showing 4 open source projects for "climate"

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    NVIDIA Earth2Studio

    NVIDIA Earth2Studio

    Open-source deep-learning framework

    NVIDIA Earth2Studio is an open-source Python package and framework designed to accelerate the development and deployment of AI-driven weather and climate science workflows. It provides a unified API that lets researchers, data scientists, and engineers build complex forecasting and analysis pipelines by combining modular prognostic and diagnostic AI models with a diverse range of real-world data sources such as global forecast systems, reanalysis datasets, and satellite feeds. The toolkit makes it easy to run deterministic and ensemble forecasts, swap models interchangeably, and process large geophysical datasets with Xarray structures, enabling experimentation with state-of-the-art deep learning models for climate and atmospheric prediction. ...
    Downloads: 8 This Week
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  • 2
    NVIDIA PhysicsNeMo

    NVIDIA PhysicsNeMo

    Open-source deep-learning framework for building and training

    ...It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations.
    Downloads: 5 This Week
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  • 3
    WFGY 3.0

    WFGY 3.0

    A tension reasoning engine over 131 S-class problems

    ...Different versions of the framework, including WFGY 1.0, 2.0, and 3.0, represent stages of development where early conceptual ideas evolved into more structured reasoning engines and diagnostic tools. The system maps reasoning tension across a large set of complex problems spanning domains such as mathematics, science, climate, finance, and artificial intelligence behavior.
    Downloads: 0 This Week
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  • 4
    Phenalysis

    Phenalysis

    Analyze agronomic plant research plots in aerial orthomosaic images.

    ...Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on Wheat in a Hot and Dry Climate. https://www.wheathub.com.au/
    Downloads: 0 This Week
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