Generative Adversarial Networks

In machine learning, generative adversarial networks (GANs) involve two artificial neural networks squaring off, one, the generator, trying to delude the other, the discriminator, into accepting synthetic data as real. Beyond their science and engineering applications, GANs can generate utterly convincing “photographs” of people who do not exist. Unrestricted use on a wide scale of... Read More

Simulated electronic health records could avoid patient privacy risks and help speed discovery. Read More