The problem they faced was that current AI techniques and architectures, deep learning algorithms and deep neural networks, are good at classifying images, but not very good at creating new ones.

Description Generative adversarial networks, or GANs, are deep learning frameworks for unsupervised learning that utilize two neural networks. The two networks are pitted against each other, with one ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Training algorithm breaks barriers to deep physical neural networks Date: December 7, 2023 Source: Ecole Polytechnique Fédérale de Lausanne Summary: Researchers have developed an algorithm to ...

In 2007, some of the leading thinkers behind deep neural networks organized an unofficial “satellite” meeting at the margins of a prestigious annual conference on artificial intelligence. The ...

The news: In a fresh spin on manufactured pop, OpenAI has released a neural network called Jukebox that can generate catchy songs in a variety of different styles, from teenybop and country to hip ...

News Release 31-Mar-2023 Metasurfaces designed by a bidirectional deep neural network and iterative algorithm for generating quantitative field distributions Peer-Reviewed Publication ...

This is where GANs come into play. How does GAN work? Ian Goodfellow’s Generative Adversarial Network technique proposes that you use two neural networks to create and refine new data. The first ...