A major challenge when working with a neural network is training the network in such a way that the resulting model doesn't over-fit the training data -- that is, generate weights and bias values that ...

Let's explore mini-batch training, the third among a variety of back-propagation algorithms you can use for training a neural network. The most common technique used to train a neural network is the ...

Crystal structure prediction (CSP) of organic molecules is a critical task, especially in pharmaceuticals and materials ...

Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots of ...

Neural networks are the core software of deep learning. Even though they’re so widespread, however, they’re really poorly understood. Researchers have observed their emergent properties without ...