How to use Spectrograms and GANs to convert Jazz to Classical Music — Introduction We have all heard about image style transfer: extracting the style from a famous painting and applying it to another image is a task that has been achcieved with a number of different methods. …

Data-driven solutions will lead the Transition to Clean Energy — Climate Change is real. And even though many scientists agree on the fact that we are already too late, people are just becoming conscious about this problem. And with the people comes politics, and with politics comes the money. That’s why in the next years there will be a major…

Audio is not so different from Images afterall — Introduction Generative Adversarial Networks, or GANs, have seen major success in the past years in the computer vision department. …

Training Generative Adversarial Networks is hard: let’s make it easier — Introduction A year ago I decided to begin my journey into the world of Generative Adversarial Networks, or GANs. I’ve always been intrigued by them since the beginning of my interest in Deep Learning, mainly for the incredible results that they could produce. …

How to generate HD images with GANs and no fancy Hardware — Introduction A number of recent studies explored some ways and techniques to generate High Definition images (1024x1024 pixels) using GANs (Generative Adversarial Networks). It’s incredibily surprising to see super realistic, HD images of human faces, animals and other things generated by an algorithm, especially remembering the first GAN images from just…

The Discriminator is more useful than you might think — Introduction A Generative Adversarial Network is an extremely interesting deep neural network architecture able to generate new data (often images) that resembles the data given during training (or in mathematical terms, matches the same distribution). Immediately after discovering GANs and how they work, I got intrigued. There is something special, maybe…