A generative adversarial network (GAN ... Figure 1: Generating Synthetic Data Using a Variational Autoencoder This article assumes you have an intermediate or better familiarity with a C-family ...

The group's first peer-reviewed paper demonstrating the application of generative models to molecules applied an adversarial autoencoder (AAE) to the generation of new promising anti-cancer ...

In his paper, Kienitz shows Gaussian mixture models ( GMM s) – a machine learning technique that has been used to fit complex ...

Generative adversarial autoencoder (AAE) architecture, an extension of generative adversarial networks, was used as the basis, and compounds with known medicinal properties and efficient ...

In this study, Insilico Medicine researchers developed a new model, the Bidirectional Adversarial Autoencoder ... provided a model that combines both generative biology and generative chemistry.

One of the more recent terms rising to prominence is Generative Adversarial Network (GAN) – but what does it mean? The principle behind the GAN was first proposed in 2014, and at its most basic ...

More often than not, these systems build upon generative adversarial networks (GANs), which are two-part AI models consisting of a generator that creates samples and a discriminator that attempts ...

From this perspective, then, it’s easy to see why generative artificial intelligence ... can manipulate a target AI by creating false or adversarial inputs to make it less effective.