GAN Lab: Generated Adversarial Networks In Your Browser!

This GitHub project is a highly interactive graphic demonstration of the features and operations of a generated adversarial network using TensorFow.js. It is based on work done by Minsuk Kahng, Nikhil Thorat, Duen Horng (Polo) Chau, Fernanda B. Viegas, and Martin Wattenberg in their paper: GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation.

Full disclosure: The data sets are small enough and simple enough to demonstrate the technology but clearly are not full-blown image processing examples, which can often consume a lot (CPU/years?) of computer time. But these small examples provide an excellent introduction into what is going on. It takes away the spooky magic…which is a good thing! 

Source de l’article sur DZONE (AI)