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    labml.ai Deep Learning Paper Implementations

    This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,

    The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.

    Screenshot

    We are actively maintaining this repo and adding new implementations almost weekly. Twitter for updates.

    Modules

    Transformers

    Recurrent Highway Networks

    LSTM

    HyperNetworks - HyperLSTM

    ResNet

    Capsule Networks

    Generative Adversarial Networks

    Sketch RNN

    Graph Neural Networks

    Counterfactual Regret Minimization (CFR)

    Solving games with incomplete information such as poker with CFR.

    Reinforcement Learning

    Optimizers

    Normalization Layers

    Distillation

    Adaptive Computation

    Uncertainty

    Installation

    pip install labml-nn

    Citing

    If you use this for academic research, please cite it using the following BibTeX entry.

    @misc{labml,
     author = {Varuna Jayasiri, Nipun Wijerathne},
     title = {labml.ai Annotated Paper Implementations},
     year = {2020},
     url = {https://nn.labml.ai/},
    }

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    🧪 labml.ai/labml

    This is a library that let's you monitor deep learning model training and hardware usage from your mobile phone. It also comes with a bunch of other tools to help write deep learning code efficiently.

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    开发语言

    • Jupyter Notebook 64.9 %
    • Python 35.1 %
    • Makefile 0.0 %