/VAE-GANS-CycleGANS

Primary LanguageJupyter Notebook

Variational Auto Encoders, GAN, and CycleGAN Implementation using Pytorch

This project demonstrates a detailed implementation of Variational Auto Encoders (VAE), Generative Adversarial Networks (GAN), and CycleGAN from scratch using Pytorch. It includes comprehensive explanations, parameter tuning processes, and extensive results visualization.

Table of Contents

VAE Implementation

VAE Idea



VAE Architecture



VAE Model plots



VAE Model Qualitative Anlaysis



GAN Implementation

GAN Idea



GAN Architecture



GAN Plots



GAN Results



CycleGAN Implementation

CycleGAN Idea


CycleGAN Plots



CycleGAN Qualitative Results



Report and Analysis

For a detailed understanding of the parameter tuning process and in-depth analysis, refer to the Project Report.

© 2023 [Yash Agrawal]