Generative Adversarial Networks (GANs) - These work by pitting two competing algorithms against each other, one tasked with generating data that resembles its training data and another tasked with ...

Insilico Medicine presented an original deep neural network architecture, Entangled Conditional Adversarial Autoencoder (ECAAE), which generates molecular structures based on various properties ...

image: Generative adversarial networks and deep reinforcement learning techniques are propagating into the many areas of pharmaceutical R&D, learning and augmenting human abilities. view more ...

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 ...

Created using generative adversarial networks (GANs) made open source by Nvidia, the website generates an invented, photo-realistic image of human being with each refresh.

ShayaKhmetov, R., et al (2020) Molecular Generation for Desired Transcriptome Changes With Adversarial Autoencoders. Frontiers in Pharmacology. doi.org/10.3389/fphar.2020.00269.

There are many new developments in the field of artificial intelligence, and one of the most exciting and transformative ideas are Generative Adversarial Networks (GANs). Here we explain in simple ...

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