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Master's coursework project on Applied Machine Learning at HCMUS: GANs - Generative Adversarial Networks

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GANs

Scope: Implement simple GAN models for Image generating

Input:

  • Training on MNIST dataset (with label 2 only)

Output:

  • An image with digit number 2

How to run:

This project contains 2 jupyter notebooks: DCGAN.ipynb and VAE_GAN.ipynb. Simply run the notebook with the desired model.

Models:

DCGAN

- Paper: https://arxiv.org/pdf/1511.06434

Architecture of models: DCGAN architecture

VAE-GAN:

- Paper: https://arxiv.org/pdf/1512.09300
- Reference code: https://github.com/rishabhd786/VAE-GAN-PYTORCH

Architecture of models: VAE-GAN architecture

Requirements

For required environement to run the Notebook, please check file requirement.txt

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Master's coursework project on Applied Machine Learning at HCMUS: GANs - Generative Adversarial Networks

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