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02456-deep-learning-project

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    • Name Last commit Last update
    .gitignore
    README.md
    Semi-supervised VAE.ipynb
    Unsupervised VAE.ipynb
    autoencoder.py
    README.md

    Un- and Semi-supervised Learning for Ultrasonic Images with Convolutional Variational Autoencoders

    Repository for project in course 02456 Deep Learning at DTU, fall 2017, by Niels Jeppesen (niejep).

    Prerequisites

    • python 3.5+
    • keras 2.0+
    • tensorflow 1.3+
    • scikit-learn 0.19+

    Files

    • autoencoder.py implements a Variational Autoencoder and a Semi-superviser Variational Autoencoder/Classifier in Keras/Tensorflow.
    • Unsupervivised VAE.ipynb is a Jupyter Notebook for recreating unsupervised MNIST result from the paper.
    • Semi-supervised VAE.ipynb is a Jupyter Notebook for recreating semi-supervised MNIST result from the paper.