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  1. A multi-task learning example for the paper

    Jupyter Notebook 435 106

  2. Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"

    Lua 349 76

  3. Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

    Python 335 94

  4. Code for Concrete Dropout as presented in

    Jupyter Notebook 197 59

  5. Dropout As A Bayesian Approximation: Code

    Shell 167 38

  6. Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.

    JavaScript 96 31

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July 2020

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