druGAN: A concept of a Generative Adversarial Autoencoder de Novo Generation of New Molecules with Desired Molecular Properties ...

Dr. James McCaffrey of Microsoft Research explains a generative adversarial network, a deep neural system that can be used to generate synthetic data for machine learning scenarios, such as generating ...

In this study, Insilico Medicine researchers developed a new model, the Bidirectional Adversarial Autoencoder, that learns a joint distribution of molecular structures and induced transcriptional ...

We propose an unsupervised method for detecting adversarial attacks in inner layers of autoencoder (AE) networks by maximizing a non-parametric measure of anomalous node activations.

Facebook has combined an “adversarial autoencoder” and a “trained-face classifier”. An autoencoder is an artificial neural network that learns a representation for a set of data unsupervised.

The Data Science Lab Generating Synthetic Data Using a Generative Adversarial Network (GAN) with PyTorch Dr. James McCaffrey of Microsoft Research explains a generative adversarial network, a deep ...