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vae-vampprior

Tensorflow implementation of the VAE with VampPrior paper (https://arxiv.org/abs/1705.07120) for the Machine Learning, Advanced Course at KTH

The model can be trained and used on 3 different datasets:

Installation

  1. Clone the repo
  2. Install python packages (listed in the requirements.txt file)
    pip install -r requirements.txt
    (or alternatevily with conda)

Information about the usage can be obtained by running python main.py -h.

Results

Here are the results obtained with stardard vae on the Frey dataset

frey1 frey2

Authors

Implemented by

  • Francesco Zappia (Standard VAE)
  • Vittorio Zampinetti (VampPrior)
  • Marco Schouten (HVAE)

More generally each of the authors influenced and contributed on each other's work.

Related pages

Part of the implementation is inspired by

License

Distributed under the MIT License. See LICENSE for more information.