The first step in training a neural network to solve a problem is usually the selection of an architecture: a specification of the number of computational ...

Generative adversarial networks (GANs) can produce remarkably realistic synthetic images. During training, a GAN pits a generator, which produces the image, ...

As machine-learning-based decision systems improve rapidly, we are discovering that it is no longer enough for them to perform well on their own. They ...

As neural networks grow in size, deploying them on-device increasingly requires special-purpose hardware that parallelizes common operations. But for ...