14. Image Denoising, Variational Autoencoder and Generative adverserial network

Lecture 56 Image Denoising

Discussion Content : Image Denoising, Image Restoration Network, Application- Low Dose CT Denoising Content File : https://drive.google.com/file/d/1xck_...

Lecture 57 Variational Autoencoder

Discussion Content : Generative models, Latent Representation, Limitation of Autoencoders, Intutition for VAE Loss Functions Content File : https://drive.google.com/file/d/1hsUO...

Lecture 58 Variational Autoencoder II

Discussion Content : Understanding latent space of Autoencoder and VAE, KL Divergence, Variational Inference Content File : https://drive.google.com/file/d/1-Maf...

Lecture 59 Variational Autoencoder III

Discussion Content : Variational Lower Bound, re-parametrization trick, Realizing VAE loss functions in terms of neural networks Content File : https://drive.google.com/file/d/1EZRd...

Lecture 60 Generative Adversarial Network

Discussion Content : Coding VAE loss functions, VAE outputs visualization, latent space vector arithmetic, Generative Adversarial Networks (GAN), Applications of GAN Content File : https://drive.google.com/file/d/1s_1f...

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