DD2434-VAE-Project (Re-Autoencoding Variational Bayes)

Project in DD2434 Advanced Machine Learning by Diogo Pinheiro, Jakob Lindén, Márk Csizmadia, and Patrick Jonsson.

Installation

In the CLI of your choice

git clone https://github.com/jakobGTO/DD2434-VAE-Project.git

Create a virtual environment (or in your base environment) with Anaconda or any virtual environment manager (see Anaconda example below):

conda create -n dd2434_vae_project python=3.8
source activate dd2434_vae_project
pip install -r requirements.txt

Usage

Use the main script to train a Variational Auto-Encoder (VAE). Set the encoder and decoder network parameters, the training parameters (e.g.: learning rate) the type of decoder (Bernoulli or Gaussian) and the data set (MNIST or Frey face) in the code.

cd DD2434-VAE-Project
python main.py

Description

The code is a replication of the research paper titled Auto-Encoding Variational Bayes (https://arxiv.org/abs/1312.6114). See the reproduced results in the report (some are also located at images/).