Showing 3 open source projects for "graph library"

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    DoWhy

    DoWhy

    DoWhy is a Python library for causal inference

    DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks. Much like machine learning libraries have done for prediction, DoWhy is a Python library that aims to spark causal thinking and analysis.
    Downloads: 1 This Week
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  • 2
    spaGO

    spaGO

    Self-contained Machine Learning and Natural Language Processing lib

    A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. In other words, it has "zero dependencies", and we are committed to keeping it that way as much as possible.
    Downloads: 1 This Week
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  • 3
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    ...UI responsiveness guarantee is sometimes obligatory when running a model. Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
    Downloads: 1 This Week
    Last Update:
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