Building Synthetic Medical Records using GANs

In this article, I'll walk you through building GANs from scratch to generate synthetic medical records using Python.

What is Fréchet inception distance (FID)? - Dataconomy

Fréchet Inception Distance (FID) is a metric that quantifies the quality and diversity of images generated by GANs by comparing feature representations.

Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models. This article…

Why WGANs beat GANs: A journey from KL divergence to Wasserstein loss

Wasserstein distance helps WGANs outperform vanilla GANs and VAEs. This post explains why so using some easy math.

Deep Convolutional GAN — How to Use a DCGAN to Generate Images in Python

An overview of DCGAN architecture with a step-by-step guide to building it yourself

Autoencoders: From Vanilla to Variational

Because GANs are not all you need

New AI tool detects Deepfakes by analyzing light reflections in the eyes

Computer scientists from the University at Buffalo used the method to successfully detect Deepfakes taken from This Person Does Not Exist.

Diving into different GAN architectures

Introduction

An End to End Introduction to GANs using Keras - MLWhiz

I bet most of us have seen a lot of AI-generated people faces in recent times, be it in papers or blogs. We have reached a stage where it is becoming increasingly difficult to distinguish between actual human faces and faces that are generated by Artificial Intelligence. In this…

Generative Adversarial Networks - The Story So Far

Nvidia’s GauGAN has been used to create 500,000 images

Nvidia's GauGAN tool has been used to create more than 500,000 images, the company announced at the SIGGRAPH 2019 conference in Los Angeles.

Generative Adversarial Networks (GANs): Engine and Applications - Data Scie

Generative adversarial networks (GANs) are a class of neural networks that are used in unsupervised machine learning. They help to solve such tasks as image generation from descriptions, getting high resolution images from low resolution ones, predicting which drug could treat a…

How Adversarial Attacks Work

Emil Mikhailov is the founder of XIX.ai [http://XIX.ai] (YC W17). Roman Trusov is a researcher at XIX.ai. Recent studies by Google Brain have shown that any machine learning classifier can be tricked to give incorrect predictions, and with a little bit of skill, you can get them…