Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

The field of artificial neural networks has seen rapid growth over the past 10-15 years. Typical applications are image processing, sound and other areas with high dimensional data. In machine ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

In this report, the neural identification problem is outlined and the identifiability question for a general class of recurrent neural networks is addressed. As part of the intelligent flight control ...

Two general approaches to combining neural networks are proposed and examined in predicting the exchange rate between the British pound and US dollar. Specifically, we propose to use systematic and ...

So how is a designer supposed to deal with what are literally thousands of options for the network architecture? Here are some guidelines for novice neural network engineers.

Neural networks have enabled a revolution in machine learning. IBM researchers show how resistive computing can be used to make them massively more powerful.