Showing 4 open source projects for "self learning"

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  • 1
    RuVector

    RuVector

    Self-Learning, Vector Graph Neural Network, and Database built in Rust

    RuVector is part of the broader rUv ecosystem of AI engineering tools and focuses on enabling advanced vector-based processing and intelligent system development within agentic and AI-driven pipelines. The project fits into a larger vision of modular, composable AI infrastructure designed to support autonomous agents, data retrieval, and intelligent automation workflows. It emphasizes extensibility and interoperability with modern AI stacks, allowing developers to integrate vector operations...
    Downloads: 3 This Week
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  • 2
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). ...
    Downloads: 0 This Week
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  • 3
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared...
    Downloads: 0 This Week
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  • 4
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already...
    Downloads: 1 This Week
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