Implementing Variational Auto Encoder from Scratch in Pytorch

In this video we look at how to go about implementing VAE in pytorch from scratch using the MNIST dataset. I also provide the repo link below where one can play with different aspects of variational auto encoder implementation in pytorch and see how it impacts the generation result as well visualize latent space of VAE , generated image manifold and interpolation results. #vae *Github Repo Link* - https://tinyurl.com/expai-repo-vae *Video on Understanding VAE* : https://youtu.be/1RPdu_5FCfk *Subscribe* - https://tinyurl.com/exai-channel-link Useful Links KL Divergence of Gaussians 1. The Kullback-Leibler divergence between Gaussians - https://tinyurl.com/gauss-vae1 2. https://tinyurl.com/gauss-vae2 3. KL Divergence between 2 Gaussian Distributions - https://tinyurl.com/gauss-vae3 Background Track Fruits of Life by Jimena Contreras Github Repo Link https://tinyurl.com/expai-repo-vae Email - [email protected]