As part of my school's Undergraduate Research Programme (URECA) at the Dauwels Lab, I studied generative adversarial networks and variational auto-encoders and their applications on disentangled representation and explainable artificial intelligence. This repository contains my implementation of GANs in PyTorch as well as a short paper on disentangled representation.
What are GANs?
Insert: Brief Intro about GANs
Insert: Short intro on Explainable AI and how generative models & GANs help.
Beyond their applications on disentangled representation, GANs and their applications are super interesting. Below are the GANs that I have implemented.
GANs Implemented
- Deep Convolutional GAN (DCGAN)
- InfoGAN
- StarGAN
- StackGAN